Search

Your search keyword '"Apgaua, DMG"' showing total 10 results
Start Over Author "Apgaua, DMG"
10 results on '"Apgaua, DMG"'

1. AusTraits, a curated plant trait database for the Australian flora

Author

Falster, D, Gallagher, R, Wenk, EH, Wright, IJ, Indiarto, D, Andrew, SC, Baxter, C, Lawson, J, Allen, S, Fuchs, A, Monro, A, Kar, F, Adams, MA, Ahrens, CW, Alfonzetti, M, Angevin, T, Apgaua, DMG, Arndt, S, Atkin, OK, Atkinson, J, Auld, T, Baker, A, von Balthazar, M, Bean, A, Blackman, CJ, Bloomfield, K, Bowman, DMJS, Bragg, J, Brodribb, TJ, Buckton, G, Burrows, G, Caldwell, E, Camac, J, Carpenter, R, Catford, JA, Cawthray, GR, Cernusak, LA, Chandler, G, Chapman, AR, Cheal, D, Cheesman, AW, Chen, SC, Choat, B, Clinton, B, Clode, PL, Coleman, H, Cornwell, WK, Cosgrove, M, Crisp, M, Cross, E, Crous, KY, Cunningham, S, Curran, T, Curtis, E, Daws, MI, DeGabriel, JL, Denton, MD, Dong, N, Du, P, Duan, H, Duncan, DH, Duncan, RP, Duretto, M, Dwyer, JM, Edwards, C, Esperon-Rodriguez, M, Evans, JR, Everingham, SE, Farrell, C, Firn, J, Fonseca, CR, French, BJ, Frood, D, Funk, JL, Geange, SR, Ghannoum, O, Gleason, SM, Gosper, CR, Gray, E, Groom, PK, Grootemaat, S, Gross, C, Guerin, G, Guja, L, Hahs, AK, Harrison, MT, Hayes, PE, Henery, M, Hochuli, D, Howell, J, Huang, G, Hughes, L, Huisman, J, Ilic, J, Jagdish, A, Jin, D, Jordan, G, Jurado, E, Kanowski, J, Kasel, S, Falster, D, Gallagher, R, Wenk, EH, Wright, IJ, Indiarto, D, Andrew, SC, Baxter, C, Lawson, J, Allen, S, Fuchs, A, Monro, A, Kar, F, Adams, MA, Ahrens, CW, Alfonzetti, M, Angevin, T, Apgaua, DMG, Arndt, S, Atkin, OK, Atkinson, J, Auld, T, Baker, A, von Balthazar, M, Bean, A, Blackman, CJ, Bloomfield, K, Bowman, DMJS, Bragg, J, Brodribb, TJ, Buckton, G, Burrows, G, Caldwell, E, Camac, J, Carpenter, R, Catford, JA, Cawthray, GR, Cernusak, LA, Chandler, G, Chapman, AR, Cheal, D, Cheesman, AW, Chen, SC, Choat, B, Clinton, B, Clode, PL, Coleman, H, Cornwell, WK, Cosgrove, M, Crisp, M, Cross, E, Crous, KY, Cunningham, S, Curran, T, Curtis, E, Daws, MI, DeGabriel, JL, Denton, MD, Dong, N, Du, P, Duan, H, Duncan, DH, Duncan, RP, Duretto, M, Dwyer, JM, Edwards, C, Esperon-Rodriguez, M, Evans, JR, Everingham, SE, Farrell, C, Firn, J, Fonseca, CR, French, BJ, Frood, D, Funk, JL, Geange, SR, Ghannoum, O, Gleason, SM, Gosper, CR, Gray, E, Groom, PK, Grootemaat, S, Gross, C, Guerin, G, Guja, L, Hahs, AK, Harrison, MT, Hayes, PE, Henery, M, Hochuli, D, Howell, J, Huang, G, Hughes, L, Huisman, J, Ilic, J, Jagdish, A, Jin, D, Jordan, G, Jurado, E, Kanowski, J, and Kasel, S

Abstract

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.

Published
2021

2. TRY plant trait database - enhanced coverage and open access

Author

Kattge, J, Bönisch, G, Díaz, S, Lavorel, S, Prentice, IC, Leadley, P, Tautenhahn, A, Werner, GDA, Aakala, T, Abedi, M, Acosta, ATR, Adamidis, GC, K, Adamson., Aiba, M, Albert, CH, Alcántara, JM, Alcázar, C, Aleixo, I, Ali, H, Amiaud, B, Ammer, C, Amoroso, MM, Anand, M, Anderson, C, Anten, N, Antos, J, Apgaua, DMG, Ashman, TL, Asmara, DH, Asner, GP, Aspinwall, M, Atkin, O, Aubin, I, Baastrup-Spohr, L, Bahalkeh, K, Bahn, M, Baker, T, Baker, WJ, Bakker, JP, Baldocchi, D, Baltzer, J, Banerjee, A, Baranger, A, Barlow, J, Barneche, DR, Baruch, Z, Bastianelli, D, Battles, J, Salguero-Gomez, R, and Terrestrial Ecology (TE)

Subjects
Access to Information, Ecology, Plan_S-Compliant-TA, international, food and beverages, Biodiversity, Plants, Ecosystem
Abstract

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Published
2020

4. Functional traits and water transport strategies in lowland tropical rainforest trees

Author

Apgaua, DMG, Ishida, FY, Tng, DYP, Laidlaw, MJ, Santos, RM, Rumman, R, Eamus, D, Holtum, JAM, and Laurance, SGW

Subjects
Plant Leaves, Tropical Climate, Rainforest, Plant Stems, General Science & Technology, Climate Change, Australia, food and beverages, Water, Plant Transpiration, Models, Biological, Trees, Droughts
Abstract

© 2015 Apgaua et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Understanding how tropical rainforest trees may respond to the precipitation extremes predicted in future climate change scenarios is paramount for their conservation and management. Tree species clearly differ in drought susceptibility, suggesting that variable water transport strategies exist. Using a multi-disciplinary approach, we examined the hydraulic variability in trees in a lowland tropical rainforest in north-eastern Australia. We studied eight tree species representing broad plant functional groups (one palm and seven eudicot mature-phase, and early-successional trees). We characterised the species' hydraulic system through maximum rates of volumetric sap flow and velocities using the heat ratio method, and measured rates of tree growth and several stem, vessel, and leaf traits. Sap flow measures exhibited limited variability across species, although early-successional species and palms had high mean sap velocities relative to most mature-phase species. Stem, vessel, and leaf traits were poor predictors of sap flow measures. However, these traits exhibited different associations in multivariate analysis, revealing gradients in some traits across species and alternative hydraulic strategies in others. Trait differences across and within tree functional groups reflect variation in water transport and drought resistance strategies. These varying strategies will help in our understanding of changing species distributions under predicted drought scenarios.

Published
2015

5. Rainforest trees respond to drought by modifying their hydraulic architecture

Author

Tng DYP, Tng DYP, Apgaua DMG, Ishida FY, Mencuccini M, Lloyd J, Laurance WF, and Laurance SGW

Subjects
fungi, food and beverages
Abstract

Increased drought is forecasted for tropical regions, with severe implications for the health and function of forest ecosystems. How mature forest trees will respond to water deficit is poorly known. We investigated wood anatomy and leaf traits in lowland tropical forest trees after 24 months of experimental rainfall exclusion. Sampling sun‐exposed young canopy branches from target species, we found species‐specific systematic variation in hydraulic‐related wood anatomy and leaf traits in response to drought stress. Relative to controls, drought‐affected individuals of different tree species variously exhibited trait measures consistent with increasing hydraulic safety. These included narrower or less vessels, reduced vessel groupings, lower theoretical water conductivities, less water storage tissue and more abundant fiber in their wood, and more occluded vessels. Drought-affected individuals also had thinner leaves, and more negative pre‐dawn or mid‐day leaf water potentials. Future studies examining both wood and leaf hydraulic traits should improve the representation of plant hydraulics within terrestrial ecosystem and biosphere models, and help fine tune predictions of how future climate changes will affect tropical forests globally.

Published
2018

6. AusTraits, a curated plant trait database for the Australian flora

Author

Falster, D, Gallagher, R, Wenk, EH, Wright, IJ, Indiarto, D, Andrew, SC, Baxter, C, Lawson, J, Allen, S, Fuchs, A, Monro, A, Kar, F, Adams, MA, Ahrens, CW, Alfonzetti, M, Angevin, T, Apgaua, DMG, Arndt, S, Atkin, OK, Atkinson, J, Auld, T, Baker, A, von Balthazar, M, Bean, A, Blackman, CJ, Bloomfield, K, Bowman, DMJS, Bragg, J, Brodribb, TJ, Buckton, G, Burrows, G, Caldwell, E, Camac, J, Carpenter, R, Catford, JA, Cawthray, GR, Cernusak, LA, Chandler, G, Chapman, AR, Cheal, D, Cheesman, AW, Chen, S-C, Choat, B, Clinton, B, Clode, PL, Coleman, H, Cornwell, WK, Cosgrove, M, Crisp, M, Cross, E, Crous, KY, Cunningham, S, Curran, Timothy, Curtis, E, Daws, MI, DeGabriel, JL, Denton, MD, Dong, N, Du, P, Duan, H, Duncan, DH, Duncan, RP, Duretto, M, Dwyer, JM, Edwards, C, Esperon-Rodriguez, M, Evans, JR, Everingham, SE, Farrell, C, Firn, J, Fonseca, CR, French, BJ, Frood, D, Funk, JL, Geange, SR, Ghannoum, O, Gleason, SM, Gosper, CR, Gray, E, Groom, PK, Grootemaat, S, Gross, C, Guerin, G, Guja, L, Hahs, AK, Harrison, MT, Hayes, PE, Henery, M, Hochuli, D, Howell, J, Huang, G, Hughes, L, Huisman, J, Ilic, J, Jagdish, A, Jin, D, Jordan, G, Jurado, E, Kanowski, J, Kasel, S, Kellermann, J, Kenny, B, Kohout, M, Kooyman, RM, Kotowska, MM, Lai, HR, Laliberté, E, Lambers, H, Lamont, BB, Lanfear, R, van Langevelde, F, Laughlin, DC, Laugier-Kitchener, B-A, Laurance, S, Lehmann, CER, Leigh, A, Leishman, MR, Lenz, T, Lepschi, B, Lewis, JD, Lim, F, Liu, U, Lord, J, Lusk, CH, Macinnis-Ng, C, McPherson, H, Magallón, S, Manea, A, López-Martinez, A, Mayfield, M, McCarthy, JK, Meers, T, van der Merwe, M, Metcalfe, DJ, Milberg, P, Mokany, K, Moles, AT, Moore, BD, Moore, N, Morgan, JW, Morris, W, Muir, A, Munroe, S, Nicholson, Á, Nicolle, D, Nicotra, AB, Niinemets, Ü, North, T, O’Reilly-Nugent, A, O’Sullivan, OS, Oberle, B, Onoda, Y, Ooi, MKJ, Osborne, CP, Paczkowska, G, Pekin, B, Guilherme Pereira, C, Pickering, C, Pickup, M, Pollock, LJ, Poot, P, Powell, JR, Power, SA, Prentice, IC, Prior, L, Prober, SM, Read, J, Reynolds, V, Richards, AE, Richardson, B, Roderick, ML, Rosell, JA, Rossetto, M, Rye, B, Rymer, PD, Sams, MA, Sanson, G, Sauquet, H, Schmidt, S, Schönenberger, J, Schulze, E-D, Sendall, K, Sinclair, S, Smith, B, Smith, R, Soper, F, Sparrow, B, Standish, RJ, Staples, TL, Stephens, R, Szota, C, Taseski, G, Tasker, E, Thomas, F, Tissue, DT, Tjoelker, MG, Tng, DYP, de Tombeur, F, Tomlinson, K, Turner, NC, Veneklaas, EJ, Venn, S, Vesk, P, Vlasveld, C, Vorontsova, MS, Warren, CA, Warwick, N, Weerasinghe, LK, Wells, J, Westoby, M, White, M, Williams, NSG, Wills, J, Wilson, PG, Yates, C, Zanne, AE, Zemunik, G, and Ziemińska, K

Full Text
View/download PDF

7. Cultural consensus and intracultural diversity in ethnotaxonomy: lessons from a fishing community in Northeast Brazil.

Author

Renck V, Apgaua DMG, Tng DYP, Bollettin P, Ludwig D, and El-Hani CN

Subjects
Animals, Brazil, Consensus, Female, Humans, Knowledge, Fisheries, Hunting
Abstract

Background: Traditional fishing communities are strongholds of ethnobiological knowledge but establishing to what degree they harbor cultural consensus about different aspects of this knowledge has been a challenge in many ethnobiological studies., Methods: We conducted an ethnobiological study in an artisanal fishing community in northeast Brazil, where we interviewed 91 community members (49 men and 42 women) with different type of activities (fishers and non-fishers), in order to obtain free lists and salience indices of the fish they know. To establish whether there is cultural consensus in their traditional knowledge on fish, we engaged a smaller subset of 45 participants in triad tasks where they chose the most different fish out of 30 triads. We used the similarity matrices generated from the task results to detect if there is cultural consensus in the way fish were classified by them., Results: The findings show how large is the community's knowledge of fish, with 197 ethnospecies registered, of which 33 species were detected as salient or important to the community. In general, men cited more fish than women. We also found that there was no cultural consensus in the ways fish were classified., Conclusions: Both free-listing and triad task methods revealed little cultural consensus in the way knowledge is structured and how fish were classified by community members. Our results suggest that it is prudent not to make assumptions that a given local community has a single cultural consensus model in classifying the organisms in their environment., (© 2022. The Author(s).)

Published
2022
Full Text
View/download PDF

8. AusTraits, a curated plant trait database for the Australian flora.

Author

Falster D, Gallagher R, Wenk EH, Wright IJ, Indiarto D, Andrew SC, Baxter C, Lawson J, Allen S, Fuchs A, Monro A, Kar F, Adams MA, Ahrens CW, Alfonzetti M, Angevin T, Apgaua DMG, Arndt S, Atkin OK, Atkinson J, Auld T, Baker A, von Balthazar M, Bean A, Blackman CJ, Bloomfield K, Bowman DMJS, Bragg J, Brodribb TJ, Buckton G, Burrows G, Caldwell E, Camac J, Carpenter R, Catford JA, Cawthray GR, Cernusak LA, Chandler G, Chapman AR, Cheal D, Cheesman AW, Chen SC, Choat B, Clinton B, Clode PL, Coleman H, Cornwell WK, Cosgrove M, Crisp M, Cross E, Crous KY, Cunningham S, Curran T, Curtis E, Daws MI, DeGabriel JL, Denton MD, Dong N, Du P, Duan H, Duncan DH, Duncan RP, Duretto M, Dwyer JM, Edwards C, Esperon-Rodriguez M, Evans JR, Everingham SE, Farrell C, Firn J, Fonseca CR, French BJ, Frood D, Funk JL, Geange SR, Ghannoum O, Gleason SM, Gosper CR, Gray E, Groom PK, Grootemaat S, Gross C, Guerin G, Guja L, Hahs AK, Harrison MT, Hayes PE, Henery M, Hochuli D, Howell J, Huang G, Hughes L, Huisman J, Ilic J, Jagdish A, Jin D, Jordan G, Jurado E, Kanowski J, Kasel S, Kellermann J, Kenny B, Kohout M, Kooyman RM, Kotowska MM, Lai HR, Laliberté E, Lambers H, Lamont BB, Lanfear R, van Langevelde F, Laughlin DC, Laugier-Kitchener BA, Laurance S, Lehmann CER, Leigh A, Leishman MR, Lenz T, Lepschi B, Lewis JD, Lim F, Liu U, Lord J, Lusk CH, Macinnis-Ng C, McPherson H, Magallón S, Manea A, López-Martinez A, Mayfield M, McCarthy JK, Meers T, van der Merwe M, Metcalfe DJ, Milberg P, Mokany K, Moles AT, Moore BD, Moore N, Morgan JW, Morris W, Muir A, Munroe S, Nicholson Á, Nicolle D, Nicotra AB, Niinemets Ü, North T, O'Reilly-Nugent A, O'Sullivan OS, Oberle B, Onoda Y, Ooi MKJ, Osborne CP, Paczkowska G, Pekin B, Guilherme Pereira C, Pickering C, Pickup M, Pollock LJ, Poot P, Powell JR, Power SA, Prentice IC, Prior L, Prober SM, Read J, Reynolds V, Richards AE, Richardson B, Roderick ML, Rosell JA, Rossetto M, Rye B, Rymer PD, Sams MA, Sanson G, Sauquet H, Schmidt S, Schönenberger J, Schulze ED, Sendall K, Sinclair S, Smith B, Smith R, Soper F, Sparrow B, Standish RJ, Staples TL, Stephens R, Szota C, Taseski G, Tasker E, Thomas F, Tissue DT, Tjoelker MG, Tng DYP, de Tombeur F, Tomlinson K, Turner NC, Veneklaas EJ, Venn S, Vesk P, Vlasveld C, Vorontsova MS, Warren CA, Warwick N, Weerasinghe LK, Wells J, Westoby M, White M, Williams NSG, Wills J, Wilson PG, Yates C, Zanne AE, Zemunik G, and Ziemińska K

Subjects
Australia, Plant Physiological Phenomena, Databases, Factual, Phenotype, Plants
Abstract

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge., (© 2021. The Author(s).)

Published
2021
Full Text
View/download PDF

9. TRY plant trait database - enhanced coverage and open access.

Author

Kattge J, Bönisch G, Díaz S, Lavorel S, Prentice IC, Leadley P, Tautenhahn S, Werner GDA, Aakala T, Abedi M, Acosta ATR, Adamidis GC, Adamson K, Aiba M, Albert CH, Alcántara JM, Alcázar C C, Aleixo I, Ali H, Amiaud B, Ammer C, Amoroso MM, Anand M, Anderson C, Anten N, Antos J, Apgaua DMG, Ashman TL, Asmara DH, Asner GP, Aspinwall M, Atkin O, Aubin I, Baastrup-Spohr L, Bahalkeh K, Bahn M, Baker T, Baker WJ, Bakker JP, Baldocchi D, Baltzer J, Banerjee A, Baranger A, Barlow J, Barneche DR, Baruch Z, Bastianelli D, Battles J, Bauerle W, Bauters M, Bazzato E, Beckmann M, Beeckman H, Beierkuhnlein C, Bekker R, Belfry G, Belluau M, Beloiu M, Benavides R, Benomar L, Berdugo-Lattke ML, Berenguer E, Bergamin R, Bergmann J, Bergmann Carlucci M, Berner L, Bernhardt-Römermann M, Bigler C, Bjorkman AD, Blackman C, Blanco C, Blonder B, Blumenthal D, Bocanegra-González KT, Boeckx P, Bohlman S, Böhning-Gaese K, Boisvert-Marsh L, Bond W, Bond-Lamberty B, Boom A, Boonman CCF, Bordin K, Boughton EH, Boukili V, Bowman DMJS, Bravo S, Brendel MR, Broadley MR, Brown KA, Bruelheide H, Brumnich F, Bruun HH, Bruy D, Buchanan SW, Bucher SF, Buchmann N, Buitenwerf R, Bunker DE, Bürger J, Burrascano S, Burslem DFRP, Butterfield BJ, Byun C, Marques M, Scalon MC, Caccianiga M, Cadotte M, Cailleret M, Camac J, Camarero JJ, Campany C, Campetella G, Campos JA, Cano-Arboleda L, Canullo R, Carbognani M, Carvalho F, Casanoves F, Castagneyrol B, Catford JA, Cavender-Bares J, Cerabolini BEL, Cervellini M, Chacón-Madrigal E, Chapin K, Chapin FS, Chelli S, Chen SC, Chen A, Cherubini P, Chianucci F, Choat B, Chung KS, Chytrý M, Ciccarelli D, Coll L, Collins CG, Conti L, Coomes D, Cornelissen JHC, Cornwell WK, Corona P, Coyea M, Craine J, Craven D, Cromsigt JPGM, Csecserits A, Cufar K, Cuntz M, da Silva AC, Dahlin KM, Dainese M, Dalke I, Dalle Fratte M, Dang-Le AT, Danihelka J, Dannoura M, Dawson S, de Beer AJ, De Frutos A, De Long JR, Dechant B, Delagrange S, Delpierre N, Derroire G, Dias AS, Diaz-Toribio MH, Dimitrakopoulos PG, Dobrowolski M, Doktor D, Dřevojan P, Dong N, Dransfield J, Dressler S, Duarte L, Ducouret E, Dullinger S, Durka W, Duursma R, Dymova O, E-Vojtkó A, Eckstein RL, Ejtehadi H, Elser J, Emilio T, Engemann K, Erfanian MB, Erfmeier A, Esquivel-Muelbert A, Esser G, Estiarte M, Domingues TF, Fagan WF, Fagúndez J, Falster DS, Fan Y, Fang J, Farris E, Fazlioglu F, Feng Y, Fernandez-Mendez F, Ferrara C, Ferreira J, Fidelis A, Finegan B, Firn J, Flowers TJ, Flynn DFB, Fontana V, Forey E, Forgiarini C, François L, Frangipani M, Frank D, Frenette-Dussault C, Freschet GT, Fry EL, Fyllas NM, Mazzochini GG, Gachet S, Gallagher R, Ganade G, Ganga F, García-Palacios P, Gargaglione V, Garnier E, Garrido JL, de Gasper AL, Gea-Izquierdo G, Gibson D, Gillison AN, Giroldo A, Glasenhardt MC, Gleason S, Gliesch M, Goldberg E, Göldel B, Gonzalez-Akre E, Gonzalez-Andujar JL, González-Melo A, González-Robles A, Graae BJ, Granda E, Graves S, Green WA, Gregor T, Gross N, Guerin GR, Günther A, Gutiérrez AG, Haddock L, Haines A, Hall J, Hambuckers A, Han W, Harrison SP, Hattingh W, Hawes JE, He T, He P, Heberling JM, Helm A, Hempel S, Hentschel J, Hérault B, Hereş AM, Herz K, Heuertz M, Hickler T, Hietz P, Higuchi P, Hipp AL, Hirons A, Hock M, Hogan JA, Holl K, Honnay O, Hornstein D, Hou E, Hough-Snee N, Hovstad KA, Ichie T, Igić B, Illa E, Isaac M, Ishihara M, Ivanov L, Ivanova L, Iversen CM, Izquierdo J, Jackson RB, Jackson B, Jactel H, Jagodzinski AM, Jandt U, Jansen S, Jenkins T, Jentsch A, Jespersen JRP, Jiang GF, Johansen JL, Johnson D, Jokela EJ, Joly CA, Jordan GJ, Joseph GS, Junaedi D, Junker RR, Justes E, Kabzems R, Kane J, Kaplan Z, Kattenborn T, Kavelenova L, Kearsley E, Kempel A, Kenzo T, Kerkhoff A, Khalil MI, Kinlock NL, Kissling WD, Kitajima K, Kitzberger T, Kjøller R, Klein T, Kleyer M, Klimešová J, Klipel J, Kloeppel B, Klotz S, Knops JMH, Kohyama T, Koike F, Kollmann J, Komac B, Komatsu K, König C, Kraft NJB, Kramer K, Kreft H, Kühn I, Kumarathunge D, Kuppler J, Kurokawa H, Kurosawa Y, Kuyah S, Laclau JP, Lafleur B, Lallai E, Lamb E, Lamprecht A, Larkin DJ, Laughlin D, Le Bagousse-Pinguet Y, le Maire G, le Roux PC, le Roux E, Lee T, Lens F, Lewis SL, Lhotsky B, Li Y, Li X, Lichstein JW, Liebergesell M, Lim JY, Lin YS, Linares JC, Liu C, Liu D, Liu U, Livingstone S, Llusià J, Lohbeck M, López-García Á, Lopez-Gonzalez G, Lososová Z, Louault F, Lukács BA, Lukeš P, Luo Y, Lussu M, Ma S, Maciel Rabelo Pereira C, Mack M, Maire V, Mäkelä A, Mäkinen H, Malhado ACM, Mallik A, Manning P, Manzoni S, Marchetti Z, Marchino L, Marcilio-Silva V, Marcon E, Marignani M, Markesteijn L, Martin A, Martínez-Garza C, Martínez-Vilalta J, Mašková T, Mason K, Mason N, Massad TJ, Masse J, Mayrose I, McCarthy J, McCormack ML, McCulloh K, McFadden IR, McGill BJ, McPartland MY, Medeiros JS, Medlyn B, Meerts P, Mehrabi Z, Meir P, Melo FPL, Mencuccini M, Meredieu C, Messier J, Mészáros I, Metsaranta J, Michaletz ST, Michelaki C, Migalina S, Milla R, Miller JED, Minden V, Ming R, Mokany K, Moles AT, Molnár A 5th, Molofsky J, Molz M, Montgomery RA, Monty A, Moravcová L, Moreno-Martínez A, Moretti M, Mori AS, Mori S, Morris D, Morrison J, Mucina L, Mueller S, Muir CD, Müller SC, Munoz F, Myers-Smith IH, Myster RW, Nagano M, Naidu S, Narayanan A, Natesan B, Negoita L, Nelson AS, Neuschulz EL, Ni J, Niedrist G, Nieto J, Niinemets Ü, Nolan R, Nottebrock H, Nouvellon Y, Novakovskiy A, Nystuen KO, O'Grady A, O'Hara K, O'Reilly-Nugent A, Oakley S, Oberhuber W, Ohtsuka T, Oliveira R, Öllerer K, Olson ME, Onipchenko V, Onoda Y, Onstein RE, Ordonez JC, Osada N, Ostonen I, Ottaviani G, Otto S, Overbeck GE, Ozinga WA, Pahl AT, Paine CET, Pakeman RJ, Papageorgiou AC, Parfionova E, Pärtel M, Patacca M, Paula S, Paule J, Pauli H, Pausas JG, Peco B, Penuelas J, Perea A, Peri PL, Petisco-Souza AC, Petraglia A, Petritan AM, Phillips OL, Pierce S, Pillar VD, Pisek J, Pomogaybin A, Poorter H, Portsmuth A, Poschlod P, Potvin C, Pounds D, Powell AS, Power SA, Prinzing A, Puglielli G, Pyšek P, Raevel V, Rammig A, Ransijn J, Ray CA, Reich PB, Reichstein M, Reid DEB, Réjou-Méchain M, de Dios VR, Ribeiro S, Richardson S, Riibak K, Rillig MC, Riviera F, Robert EMR, Roberts S, Robroek B, Roddy A, Rodrigues AV, Rogers A, Rollinson E, Rolo V, Römermann C, Ronzhina D, Roscher C, Rosell JA, Rosenfield MF, Rossi C, Roy DB, Royer-Tardif S, Rüger N, Ruiz-Peinado R, Rumpf SB, Rusch GM, Ryo M, Sack L, Saldaña A, Salgado-Negret B, Salguero-Gomez R, Santa-Regina I, Santacruz-García AC, Santos J, Sardans J, Schamp B, Scherer-Lorenzen M, Schleuning M, Schmid B, Schmidt M, Schmitt S, Schneider JV, Schowanek SD, Schrader J, Schrodt F, Schuldt B, Schurr F, Selaya Garvizu G, Semchenko M, Seymour C, Sfair JC, Sharpe JM, Sheppard CS, Sheremetiev S, Shiodera S, Shipley B, Shovon TA, Siebenkäs A, Sierra C, Silva V, Silva M, Sitzia T, Sjöman H, Slot M, Smith NG, Sodhi D, Soltis P, Soltis D, Somers B, Sonnier G, Sørensen MV, Sosinski EE Jr, Soudzilovskaia NA, Souza AF, Spasojevic M, Sperandii MG, Stan AB, Stegen J, Steinbauer K, Stephan JG, Sterck F, Stojanovic DB, Strydom T, Suarez ML, Svenning JC, Svitková I, Svitok M, Svoboda M, Swaine E, Swenson N, Tabarelli M, Takagi K, Tappeiner U, Tarifa R, Tauugourdeau S, Tavsanoglu C, Te Beest M, Tedersoo L, Thiffault N, Thom D, Thomas E, Thompson K, Thornton PE, Thuiller W, Tichý L, Tissue D, Tjoelker MG, Tng DYP, Tobias J, Török P, Tarin T, Torres-Ruiz JM, Tóthmérész B, Treurnicht M, Trivellone V, Trolliet F, Trotsiuk V, Tsakalos JL, Tsiripidis I, Tysklind N, Umehara T, Usoltsev V, Vadeboncoeur M, Vaezi J, Valladares F, Vamosi J, van Bodegom PM, van Breugel M, Van Cleemput E, van de Weg M, van der Merwe S, van der Plas F, van der Sande MT, van Kleunen M, Van Meerbeek K, Vanderwel M, Vanselow KA, Vårhammar A, Varone L, Vasquez Valderrama MY, Vassilev K, Vellend M, Veneklaas EJ, Verbeeck H, Verheyen K, Vibrans A, Vieira I, Villacís J, Violle C, Vivek P, Wagner K, Waldram M, Waldron A, Walker AP, Waller M, Walther G, Wang H, Wang F, Wang W, Watkins H, Watkins J, Weber U, Weedon JT, Wei L, Weigelt P, Weiher E, Wells AW, Wellstein C, Wenk E, Westoby M, Westwood A, White PJ, Whitten M, Williams M, Winkler DE, Winter K, Womack C, Wright IJ, Wright SJ, Wright J, Pinho BX, Ximenes F, Yamada T, Yamaji K, Yanai R, Yankov N, Yguel B, Zanini KJ, Zanne AE, Zelený D, Zhao YP, Zheng J, Zheng J, Ziemińska K, Zirbel CR, Zizka G, Zo-Bi IC, Zotz G, and Wirth C

Subjects
Biodiversity, Ecology, Plants, Access to Information, Ecosystem
Abstract

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Published
2020
Full Text
View/download PDF

10. Elevated temperature and CO2 cause differential growth stimulation and drought survival responses in eucalypt species from contrasting habitats.

Author

Apgaua DMG, Tng DYP, Forbes SJ, Ishida YF, Vogado NO, Cernusak LA, and Laurance SGW

Subjects
Carbon Dioxide, Photosynthesis, Seedlings, Temperature, Droughts, Eucalyptus
Abstract

Climate change scenarios predict increasing atmospheric CO2 concentrations ([CO2]), temperatures and droughts in tropical regions. Individually, the effects of these climate factors on plants are well established, whereas experiments on the interactive effects of a combination of factors are rare. Moreover, how these environmental factors will affect tree species along a wet to dry gradient (e.g., along tropical forest-savanna transitions) remains to be investigated. We hypothesized that under the simulated environmental conditions, plant growth, physiological performance and survivorship would vary in a manner consistent with the species' positions of origin along this gradient. In a glasshouse experiment, we raised seedlings of three Eucalyptus species, each occurring naturally in a wet forest, savanna and forest-savanna ecotone, respectively. We evaluated the effect of drought, elevated temperature (4 °C above ambient glasshouse temperature of 22 °C) and elevated temperature in combination with elevated [CO2] (400 ppm [CO2] above ambient of 400 ppm), on seedling growth, survivorship and physiological responses (photosynthesis, stomatal conductance and water-use efficiency). Elevated temperature under ambient [CO2] had little effect on growth, biomass and plant performance of well-watered seedlings, but hastened mortality in drought-affected seedlings, affecting the forest and ecotone more strongly than the savanna species. In contrast, elevated [CO2] in combination with elevated temperatures delayed the appearance of drought stress symptoms and enhanced survivorship in drought-affected seedlings, with the savanna species surviving the longest, followed by the ecotone and forest species. Elevated [CO2] in combination with elevated temperatures also enhanced growth and biomass and photosynthesis in well-watered seedlings of all species, but modified shoot:root biomass partitioning and stomatal conductance differentially across species. Our study highlights the need for a better understand of the interactive effects of elevated [CO2], temperature and drought on plants and the potential to upscale these insights for understanding biome changes., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results