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 in | Journal of vegetation science Vol. 28; no. 5; pp. 1082 - 1095 |
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Main Authors | , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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Hoboken
John Wiley & Sons Ltd
01.09.2017
Wiley Subscription Services, Inc |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Bill surname: Shipley fullname: Shipley, Bill – sequence: 2 givenname: Michael surname: Belluau fullname: Belluau, Michael – sequence: 3 givenname: Ingolf surname: Kühn fullname: Kühn, Ingolf – sequence: 4 givenname: Nadejda A. surname: Soudzilovskaia fullname: Soudzilovskaia, Nadejda A. – sequence: 5 givenname: Michael surname: Bahn fullname: Bahn, Michael – sequence: 6 givenname: Josep surname: Penuelas fullname: Penuelas, Josep – sequence: 7 givenname: Jens surname: Kattge fullname: Kattge, Jens – sequence: 8 givenname: Lawren surname: Sack fullname: Sack, Lawren – sequence: 9 givenname: Jeannine surname: Cavender-Bares fullname: Cavender-Bares, Jeannine – sequence: 10 givenname: Wim A. surname: Ozinga fullname: Ozinga, Wim A. – sequence: 11 givenname: Benjamin surname: Blonder fullname: Blonder, Benjamin – sequence: 12 givenname: Peter M. surname: van Bodegom fullname: van Bodegom, Peter M. – sequence: 13 givenname: Peter surname: Manning fullname: Manning, Peter – sequence: 14 givenname: Thomas surname: Hickler fullname: Hickler, Thomas – sequence: 15 givenname: Enio surname: Sosinski fullname: Sosinski, Enio – sequence: 16 givenname: Valério surname: De Patta Pillar fullname: De Patta Pillar, Valério – sequence: 17 givenname: Vladimir surname: Onipchenko fullname: Onipchenko, Vladimir – sequence: 18 givenname: Peter surname: Poschlod fullname: Poschlod, Peter |
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Copyright | Copyright © 2017 International Association for Vegetation Science 2017 International Association for Vegetation Science 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 |
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