Aligning quantitative vegetation classification and landscape scale mapping: updating the classification approach of the Regional Ecosystem classification system used in Queensland
Eda Addicott
A B C D , Victor John Neldner A and Timothy Ryan A
+ Author Affiliations
- Author Affiliations
A Queensland Herbarium, Mt Coot-tha Road, Toowong, Department of Environment & Science, Queensland Government, Qld 4066, Australia.
B Australian Tropical Herbarium, James Cook University, Cairns, Qld 4870, Australia.
C Centre for Tropical Environmental and Sustainability Science (TESS) and College of Science & Engineering, James Cook University, PO Box 6811, Cairns, Qld 4870, Australia.
D Corresponding author. Email: eda.addicott@des.qld.gov.au
Australian Journal of Botany 69(7) 400-413 https://doi.org/10.1071/BT20108
Submitted: 22 August 2020 Accepted: 15 February 2021 Published: 11 May 2021
Journal Compilation © CSIRO 2021 Open Access CC BY
Abstract
Vegetation classification systems form a base for conservation management and the ecological exploration of the patterns and drivers of species’ distributions. A standardised system crossing administrative and geographical boundaries is widely recognised as most useful for broad-scale management. The Queensland Government, recognising this, uses the Regional Ecosystem (RE) classification system and accompanying mapping as a state-wide standardised vegetation classification system. This system informs legislation and policy at local, state and national levels, underpinning decisions that have wide-ranging implications for biodiversity and people’s livelihoods. It therefore needs to be robust from a scientific and legal perspective. The current approach in the RE system for identifying vegetation communities relies on expert-based class definition procedures. This is in contrast to best practice, which is based on quantitative procedures. This paper discusses the RE system in a global context and outlines the updated approach that incorporates quantitative class definition procedures, synthesises the research behind the updated approach and discusses its implications and implementation.
Keywords: Queensland, Qld, mapping, class definition procedures, vegetation communities, plant association, conservation management, classification system.
References
Accad A, Neldner VJ, Kelley JAR, Li J, Richter D (2019) Remnant regional ecosystem vegetation in Queensland. Analysis 1997–2017. (Queensland Department of Environment and Science: Brisbane, Qld, Australia) Available at https://www.qld.gov.au/environment/plants-animals/plants/ecosystems/remnant-vegetation [Verified 18 March 2021]Addicott E (2020) A new classification approach: Improving the Regional Ecosystem Classification in Queensland, Australia. PhD thesis. James Cook University, Cairns, Qld, Australia.
Addicott E, Laurance SGW (2019) Supervised versus un-supervised classification: a quantitative comparison of plant communities in savanna vegetation. Applied Vegetation Science 22, 373–382.
| Supervised versus un-supervised classification: a quantitative comparison of plant communities in savanna vegetation.Crossref | GoogleScholarGoogle Scholar |
Addicott E, Newton M, Laurance S, Neldner J, Laidlaw M, Butler D (2018a) A new classification of savanna plant communities on the igneous rock lowlands and Tertiary sandy plain landscapes of Cape York Peninsula bioregion. Cunninghamia 18, 29–72.
Addicott E, Laurance S, Lyons M, Butler D, Neldner J (2018b) When rare species are not important: Linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation. Community Ecology 19, 67–76.
| When rare species are not important: Linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation.Crossref | GoogleScholarGoogle Scholar |
Addicott E, Laurance SGW, Bannink P, Thompson S (2020) The intertidal plant communities in north-eastern Australia, their carbon stores and vulnerability to extreme climate events. Aquatic Conservation 30, 2298–2312.
| The intertidal plant communities in north-eastern Australia, their carbon stores and vulnerability to extreme climate events.Crossref | GoogleScholarGoogle Scholar |
Aho K, Roberts DW, Weaver T (2008) Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods. Journal of Vegetation Science 19, 549–562.
| Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods.Crossref | GoogleScholarGoogle Scholar |
Beadle NCW (1981) ‘The vegetation of Australia.’ (Cambridge University Press: New York, NY, USA)
Beard JS (1973) The Physiognomic Approach. In ‘Classification of Plant Communities. Handbook of Vegetation Science’. (Ed. RH Whittaker) pp. 33–64. (Junk: The Hague, Netherlands).
Bedward M, Keith DA, Pressey RL (1992) Homogeneity analysis: assessing the utility of classifications and maps of natural resources. Australian Journal of Ecology 17, 133–139.
| Homogeneity analysis: assessing the utility of classifications and maps of natural resources.Crossref | GoogleScholarGoogle Scholar |
Belbin L, McDonald C (1993) Comparing three classification strategies for use in ecology. Journal of Vegetation Science 4, 341–348.
| Comparing three classification strategies for use in ecology.Crossref | GoogleScholarGoogle Scholar |
Brown LR, Bredenkamp GJ (2018) An overview of the vegetation classification approach in South Africa. Phytocoenologia 48, 163–170.
| An overview of the vegetation classification approach in South Africa.Crossref | GoogleScholarGoogle Scholar |
Carpenter G, Gillison AN, Winter J (1993) DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals. Biodiversity and Conservation 2, 667–680.
| DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals.Crossref | GoogleScholarGoogle Scholar |
Cavada N, Ciolli M, Rocchini D, Barelli C, Marshall AR, Rovero F (2017) Integrating field and satellite data for spatially explicit inference on the density of threatened arboreal primates. Ecological Applications 27, 235–243.
| Integrating field and satellite data for spatially explicit inference on the density of threatened arboreal primates.Crossref | GoogleScholarGoogle Scholar | 28052505PubMed |
Chytrý M, Tichý L (2018) National vegetation classification of the Czech Republic: a summary of the approach. Phytocoenologia 48, 121–131.
| National vegetation classification of the Czech Republic: a summary of the approach.Crossref | GoogleScholarGoogle Scholar |
Chytrý M, Schaminee JHJ, Schwabe A (2011) Vegetation survey: a new focus for applied vegetation science. Applied Vegetation Science 14, 435–439.
| Vegetation survey: a new focus for applied vegetation science.Crossref | GoogleScholarGoogle Scholar |
Chytrý M, Chiarucci A, Pärtel M, Pillar VD, Bakker JP, Mucina L, Peet RK, White PS (2019) Progress in vegetation science: trends over the past three decades and new horizons. Journal of Vegetation Science 30, 1–4.
| Progress in vegetation science: trends over the past three decades and new horizons.Crossref | GoogleScholarGoogle Scholar |
Clarke KR, Gorley RN (2006) ‘PRIMER v6: User Manual and Tutorial.’ (PRIMER-E Ltd: Plymouth, UK)
Clarke KR, Gorley RN (2015) ‘PRIMER v7: User Manual and Tutorial.’ (PRIMER-E Ltd: Plymouth, UK)
Clarke KR, Somerfield PJ, Gorley RN (2008) Testing of null hypotheses in exploratory community analyses: similarity profiles and biota-environment linkage. Journal of Experimental Marine Biology and Ecology 366, 56–69.
| Testing of null hypotheses in exploratory community analyses: similarity profiles and biota-environment linkage.Crossref | GoogleScholarGoogle Scholar |
Clarke KR, Gorley RN, Somerfield PJ, Warwick RM (2014) ‘Change in Marine Communities. An Approach to Statistical Analysis and Interpretation.’ (PRIMER-E: Plymouth, UK)
De Cáceres M, Wiser SK (2012) Towards consistency in vegetation classification. Journal of Vegetation Science 23, 387–393.
| Towards consistency in vegetation classification.Crossref | GoogleScholarGoogle Scholar |
De Cáceres M, Font X, Oliva F (2010) The management of vegetation classifications with fuzzy clustering. Journal of Vegetation Science 21, 1138–1151.
| The management of vegetation classifications with fuzzy clustering.Crossref | GoogleScholarGoogle Scholar |
De Cáceres M, Legendre P, He F, Faith D (2013) Dissimilarity measurements and the size structure of ecological communities. Methods in Ecology and Evolution 4, 1167–1177.
| Dissimilarity measurements and the size structure of ecological communities.Crossref | GoogleScholarGoogle Scholar |
De Cáceres M, Chytrý M, Agrillo E, Attorre F, Botta-Dukát Z, Capelo J, Czúcz B, Dengler J, Ewald J, Faber-Langendoen D, Feoli E, Franklin SB, Gavilán R, Gillet F, Jansen F, Jiménez-Alfaro B, Krestov P, Landucci F, Lengyel A, Loidi J, Mucina L, Peet RK, Roberts DW, Roleček J, Schaminée JHJ, Schmidtlein S, Theurillat JP, Tichý L, Walker DA, Wildi O, Willner W, Wiser SK (2015) A comparative framework for broad-scale plot-based vegetation classification. Applied Vegetation Science 18, 543–560.
| A comparative framework for broad-scale plot-based vegetation classification.Crossref | GoogleScholarGoogle Scholar |
De Cáceres M, Franklin SB, Hunter JT, Landucci F, Dengler J, Roberts DW (2018) Global overview of plot-based vegetation classification approaches. Phytocoenologia 48, 101–112.
| Global overview of plot-based vegetation classification approaches.Crossref | GoogleScholarGoogle Scholar |
Dufrêne M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecological Monographs 67, 345–366.
| Species assemblages and indicator species: the need for a flexible asymmetrical approach.Crossref | GoogleScholarGoogle Scholar |
Eldridge DJ, Delgado-Baquerizo M, Travers SK, Val J, Oliver I (2018) Livestock grazing and forest structure regulate the assembly of ecological clusters within plant networks in eastern Australia. Journal of Vegetation Science 29, 788–797.
| Livestock grazing and forest structure regulate the assembly of ecological clusters within plant networks in eastern Australia.Crossref | GoogleScholarGoogle Scholar |
European Vegetation Survey Working Group (2017) Procedures for updating the standard European vegetation classification (draft). Available at http://euroveg.org/news#70 [Verified 9 August 2017].
Executive Steering Committee for Australian Vegetation Information, Department of the Environment and Heritage (2003) Australian Vegetation Attribute Manual: National Vegetation Information System, Version 6.0. (Executive Steering Committee for Australian Vegetation Information: Canberra, ACT, Australia) Available at https://environment.gov.au/system/files/pages/06613354-b8a0-4a0e-801e-65b118a89a2f/files/vegetation-attribute-manual-6.pdf [Verified 15 August 2020]
Faber-Langendoen D, Keeler-Wolf T, Meidinger D, Tart D, Hoagland B, Josse C, Navarro G, Ponomarenko S, Saucier J-P, Weakley A, Comer P (2014) EcoVeg: a new approach to vegetation description and classification. Ecological Monographs 84, 533–561.
| EcoVeg: a new approach to vegetation description and classification.Crossref | GoogleScholarGoogle Scholar |
Feoli E, Zuccarello V (1991) Syntaxonomy: a source of useful fuzzy sets for environmental analysis? In ‘Computer Assisted Vegetation Analysis’. (Eds E Feoli, L Orloci) pp. 265–271. (Kluwer: Dordrecht, Netherlands).
Field JG, Clarke KR, Warwick RM (1982) A practical strategy for analysing multispecies distribution patterns. Marine Ecology Progress Series 8, 37–52.
| A practical strategy for analysing multispecies distribution patterns.Crossref | GoogleScholarGoogle Scholar |
Franklin S (2015) How a national vegetation classification can help ecological research and management. Frontiers in Ecology and the Environment 13, 185–186.
| How a national vegetation classification can help ecological research and management.Crossref | GoogleScholarGoogle Scholar |
Gauch HG, Whittaker RH (1981) Hierarchical classification of community data. Journal of Ecology 69, 537–557.
| Hierarchical classification of community data.Crossref | GoogleScholarGoogle Scholar |
Gellie NJH, Hunter JT, Benson JS, Kirkpatrick JB, Cheal DC, McCreery K, Brocklehurst P (2018) Overview of plot-based vegetation classification approaches within Australia. Phytocoenologia 48, 251–272.
| Overview of plot-based vegetation classification approaches within Australia.Crossref | GoogleScholarGoogle Scholar |
Gillet F, Julve P (2018) The integrated synusial approach to vegetation classification and analysis. Phytocoenologia 48, 141–152.
| The integrated synusial approach to vegetation classification and analysis.Crossref | GoogleScholarGoogle Scholar |
Goodall DW (1973) Numerical Classification. In ‘Ordination and Classification of Communities. Handbook of Vegetation Science’. (Ed. RH Whittaker) pp. 575–615. (Junk: The Hague, Netherlands).
Goodall DW (2014) A century of vegetation science. Journal of Vegetation Science 25, 913–916.
| A century of vegetation science.Crossref | GoogleScholarGoogle Scholar |
Grime JP (1998) Benefits of Plant Diversity to Ecosystems: immediate, filter and founder effects. Journal of Ecology 86, 902–910.
| Benefits of Plant Diversity to Ecosystems: immediate, filter and founder effects.Crossref | GoogleScholarGoogle Scholar |
Guarino R, Willner W, Pignatti S, Attorre F, Loidi JJ (2018) Spatio-temporal variations in the application of the Braun-Blanquet approach in Europe. Phytocoenologia 48, 239–250.
| Spatio-temporal variations in the application of the Braun-Blanquet approach in Europe.Crossref | GoogleScholarGoogle Scholar |
Guo K, Liu C-C, Xie Z-Q, Li FY, Franklin SB, Lu Z-J, Ma K-P (2018) China Vegetation Classification: concept, approach and applications. Phytocoenologia 48, 113–120.
| China Vegetation Classification: concept, approach and applications.Crossref | GoogleScholarGoogle Scholar |
Hnatiuk RJ, Thackway R, Walker J (2009) Vegetation. In ‘Australian Soil and Land Survey Field Handbook’. (Ed. National Committee on Soil and Terrain) pp. 73–125. (CSIRO Publishing: Melbourne, Vic., Australia)
Hunter JT, Lechner AM (2018) A multiscale, hierarchical, ecoregional and floristic classification of arid and semi-arid ephemeral wetlands in New South Wales, Australia. Marine and Freshwater Research 69, 418–431.
| A multiscale, hierarchical, ecoregional and floristic classification of arid and semi-arid ephemeral wetlands in New South Wales, Australia.Crossref | GoogleScholarGoogle Scholar |
Hüttich C, Herold M, Wegmann M, Cord A, Strohbach B, Schmullius C, Dech S (2011) Assessing effects of temporal compositing and varying observation periods for large-area land-cover mapping in semi-arid ecosystems: Implications for global monitoring. Remote Sensing of Environment 115, 2445–2459.
| Assessing effects of temporal compositing and varying observation periods for large-area land-cover mapping in semi-arid ecosystems: Implications for global monitoring.Crossref | GoogleScholarGoogle Scholar |
Kent M (2012) ‘Vegetation Description and Data Analysis: a Practical Approach.’ (Wiley-Blackwell: Oxford, UK)
Kočí M, Chytrý M, Tichý L (2003) Formalized reproduction of an expert-based phytosociological classification: a case study of subalpine tall-forb vegetation. Journal of Vegetation Science 14, 601–610.
| Formalized reproduction of an expert-based phytosociological classification: a case study of subalpine tall-forb vegetation.Crossref | GoogleScholarGoogle Scholar |
Kuchler AW (1951) The relation between classifying and mapping vegetation. Ecology 32, 275–283.
| The relation between classifying and mapping vegetation.Crossref | GoogleScholarGoogle Scholar |
Küchler AW, Zonneveld IS (1988) ‘Vegetation Mapping.’ (Kluwer: Dordrecht, Netherlands)
Landucci F, Tichý L, Šumberová K, Chytrý M (2015) Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation. Journal of Vegetation Science 26, 791–803.
| Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation.Crossref | GoogleScholarGoogle Scholar |
Lehmann CER, Felfili J, Hutley LB, Ratnam J, San Jose J, Montes R, Franklin D, Russell-Smith J, Ryan CM, Durigan G, Hiernaux P, Anderson TM, Haidar R, Bowman DMJS, Bond WJ, Sankaran M, Higgins SI, Archibald S, Hoffmann WA, Hanan NP, Williams RJ, Fensham RJ (2014) Savanna vegetation-fire-climate relationships differ among continents. Science 343, 548–552.
| Savanna vegetation-fire-climate relationships differ among continents.Crossref | GoogleScholarGoogle Scholar |
Lepš J (2008) Diversity and ecosystem function. In ‘Vegetation Ecology’. (Ed. E van der Maarel) pp. 199–237. (Wiley-Blackwell: Oxford, UK)
Lewis DL (2012) An evaluation of image and field data for vegetation community mapping in tropical savannas. PhD thesis. University of Queensland, Brisbane, Qld, Australia. Available at https://espace.library.uq.edu.au/view/UQ:301982.
Lötter MC, Mucina L, Witkowski ETF (2013) The classification conundrum: species fidelity as leading criterion in search of a rigorous method to classify a complex forest data set. Community Ecology 14, 121–132.
| The classification conundrum: species fidelity as leading criterion in search of a rigorous method to classify a complex forest data set.Crossref | GoogleScholarGoogle Scholar |
Lyons M, Keith DA, Warton DI, Somerville M, Kingsford RT (2016) Model-based assessment of ecological community classifications. Journal of Vegetation Science 27, 704–715.
| Model-based assessment of ecological community classifications.Crossref | GoogleScholarGoogle Scholar |
MacKenzie WH, Meidinger DV (2018) The Biogeoclimatic Ecosystem classification approach: an ecological framework for vegetation classification. Phytocoenologia 48, 203–213.
| The Biogeoclimatic Ecosystem classification approach: an ecological framework for vegetation classification.Crossref | GoogleScholarGoogle Scholar |
Marignani M, Del Vico E, Maccherini S (2008) Performance of indicators and the effect of grain size in the discrimination of plant communities for restoration purposes. Community Ecology 9, 201–206.
| Performance of indicators and the effect of grain size in the discrimination of plant communities for restoration purposes.Crossref | GoogleScholarGoogle Scholar |
Mariotte P (2014) Do subordinate species punch above their weight? Evidence from above‐ and below‐ground. New Phytologist 203, 16–21.
| Do subordinate species punch above their weight? Evidence from above‐ and below‐ground.Crossref | GoogleScholarGoogle Scholar |
McCune B, Grace JB (2002) ‘Analysis of Ecological Communities.’ (MjM Software Design)
Memiaghe HR, Lutz JA, Korte L, Alonso A, Kenfack D (2016) Ecological importance of small-diameter trees to the structure, diversity and biomass of a tropical evergreen forest at Rabi, Gabon. PLoS One 11, e0154988
| Ecological importance of small-diameter trees to the structure, diversity and biomass of a tropical evergreen forest at Rabi, Gabon.Crossref | GoogleScholarGoogle Scholar | 27186658PubMed |
Moraczewski IR (1993) Fuzzy logic for phytosociology – 1. Syntaxa as vague concepts. Vegetatio 106, 1–11.
| Fuzzy logic for phytosociology – 1. Syntaxa as vague concepts.Crossref | GoogleScholarGoogle Scholar |
Mucina L (1997) Classification of vegetation: past, present and future. Journal of Vegetation Science 8, 751–760.
| Classification of vegetation: past, present and future.Crossref | GoogleScholarGoogle Scholar |
Mucina L, Daniel G (2013) ‘Vegetation Mapping in the Northern Kimberley, Western Australia.’ (Ed. L Mucina) (Curtin University: Perth, WA)
Mucina L, Tichý L (2018) Forest classification: data-analytical experiments on vertical forest layering and flattened data. In ‘Vegetation Survey and Classification of Subtropical Forests of Southern Africa’. (Ed. L Mucina) pp. 47–57. (Springer).
Mucina L, Bültmann H, Dierssen K, Theurillat J-P, Raus T, Carni A, Šumberová K, Willner W, Dengler J, Schaminee JHJ, Hennekens SM (2016) Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities. Applied Vegetation Science 19, 3–264.
| Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities.Crossref | GoogleScholarGoogle Scholar |
Neldner V (2014) The contribution of vegetation survey and mapping to Herbarium collections and botanical knowledge: a case study from Queensland. Cunninghamia 14, 77–87.
| The contribution of vegetation survey and mapping to Herbarium collections and botanical knowledge: a case study from Queensland.Crossref | GoogleScholarGoogle Scholar |
Neldner VJ, Butler DW (2008) Is 500 m2 an effective plot size to sample florisitic diversity for Queensland’s vegetation? Cunninghamia 10, 513–519.
Neldner VJ, Howitt CJ (1991) Comparision of an intuitive mapping classification and numerical classifications of vegetation in south-east Queensland, Australia. Vegetatio 94, 141–152.
| Comparision of an intuitive mapping classification and numerical classifications of vegetation in south-east Queensland, Australia.Crossref | GoogleScholarGoogle Scholar |
Neldner VJ, Fensham RJ, Clarkson JR, Stanton JP (1997) The natural grasslands of Cape York Peninsula, Australia. Description, distribution and conservation status. Biological Conservation 81, 121–136.
| The natural grasslands of Cape York Peninsula, Australia. Description, distribution and conservation status.Crossref | GoogleScholarGoogle Scholar |
Neldner VJ, Kirkwood AB, Collyer BS (2004) Optimum time for sampling floristic diversity in tropical eucalypt woodlands of northern Queensland. The Rangeland Journal 26, 190–203.
| Optimum time for sampling floristic diversity in tropical eucalypt woodlands of northern Queensland.Crossref | GoogleScholarGoogle Scholar |
Neldner VJ, Butler DW, Guymer GP (2017) Queensland’s regional ecosystems: Building and maintaining a biodiversity inventory, planning framework and information system for Queensland. Ver. 2.0. (Queensland Herbarium, Department of Environment and Science: Brisbane, Australia) Available at https://www.qld.gov.au/environment/plants-animals/plants/herbarium/publications [Verified 15 August 2020]
Neldner VJ, Niehus RE, Wilson BA, McDonald WJF, Ford AJ, Accad AN (2019) The vegetation of Queensland: descriptions of broad vegetation groups. Ver. 4.0. (Queensland Herbarium Department of Environment and Science) Available at https://www.publications.qld.gov.au/dataset/redd/resource/78209e74-c7f2-4589-90c1-c33188359086 [Verified 18 March 2021]
Neldner VJ, Wilson BA, Dillewaard HA, Ryan TS, Butler DW, McDonald WJF, Addicott E, Appelman CN (2020) Methodology for survey and mapping of vegetation communities and regional ecosystems in Queensland. Ver. 5.1. Available at https://www.publications.qld.gov.au/dataset/redd/resource/6dee78ab-c12c-4692-9842-b7257c2511e4 [Verified 18 March 2021]
Nezerkova-Hejcmanova P, Hejcman M, Camara AA, Antonínová M, Pavlů V, Černý T, Bâ AT (2005) Analysis of the herbaceous undergrowth of the woody savanna in the Fathala Reserve, Delta du Saloum National Park (Senegal). Belgian Journal of Botany 138, 119–128.
Office of Environment & Heritage, NSW Office of Environment and Heritage (2018) NSW plant community type – change control. Available at http://www.environment.nsw.gov.au/research/PCTchangecontrol.htm [Verified 15 August 2020]
Oliver I, Broese EA, Dillon ML, Sivertsen D, McNellie MJ (2013) Semi-automated assignment of vegetation survey plots within an a priori classification of vegetation types. Methods in Ecology and Evolution 4, 73–81.
| Semi-automated assignment of vegetation survey plots within an a priori classification of vegetation types.Crossref | GoogleScholarGoogle Scholar |
Peet RK, Roberts DW (2013) Classification of natural and semi-natural vegetation. In ‘Vegetation Ecology’. (Eds E van der Maarel, J Franklin) pp. 28–70. (Wiley: Chichester, UK)
Peet RK, Palmquist KA, Wentworth TR, Schafale MP, Weakley AS, Lee MT (2018) Carolina vegetation survey: an initiative to improve regional implementation of the US National Vegetation Classification. Phytocoenologia 48, 171–179.
| Carolina vegetation survey: an initiative to improve regional implementation of the US National Vegetation Classification.Crossref | GoogleScholarGoogle Scholar |
Penn MG, Sutton DA, Monro A (2004) Vegetation of the Greater Maya Mountains, Belize. Systematics and Biodiversity 2, 21–44.
| Vegetation of the Greater Maya Mountains, Belize.Crossref | GoogleScholarGoogle Scholar |
Pos E, Andino JEG, Sabatier D, Molino JF, Pitman N, Mogollon H, Neill D, Ceron C, Rivas G, Di Fiore A, Thomas R, Tirado M, Young KR, Wang O, Sierra R, Garcia-Villacorta R, Zagt R, Palacios W, Aulestia M, ter Steege H (2014) Are all species necessary to reveal ecologically important patterns? Ecology and Evolution 4, 4626–4636.
| Are all species necessary to reveal ecologically important patterns?Crossref | GoogleScholarGoogle Scholar | 25558357PubMed |
Queensland Herbarium (2019) Regional Ecosystem Description Database (REDD). Ver. 11.1. Available at https://apps.des.qld.gov.au/regional-ecosystems/ [Verified 15 August 2020]
Roberts DW (2015) Vegetation classification by two new iterative reallocation optimization algorithms. Plant Ecology 216, 741–758.
| Vegetation classification by two new iterative reallocation optimization algorithms.Crossref | GoogleScholarGoogle Scholar |
Rodwell JS (2018) The UK national vegetation classification. Phytocoenologia 48, 133–140.
| The UK national vegetation classification.Crossref | GoogleScholarGoogle Scholar |
Roleček J, Chytrý M, Hájek M, Lvončik S, Tichý L (2007) Sampling design in large-scale vegetation studies: do not sacrifice ecological thinking to statistical purism. Folia Geobotanica 42, 199–208.
| Sampling design in large-scale vegetation studies: do not sacrifice ecological thinking to statistical purism.Crossref | GoogleScholarGoogle Scholar |
Sattler PS, Williams RD (1999) ‘The Conservation Status of Queensland’s Bioregional Ecosystems.’ (Environmental Protection Agency: Brisbane, Qld, Australia)
Smartt PFM, Meacock SE, Lambert JM (1974) Investigations into the properties of quantitative vegetational data: I. Pilot study. Journal of Ecology 62, 735–759.
| Investigations into the properties of quantitative vegetational data: I. Pilot study.Crossref | GoogleScholarGoogle Scholar |
Smartt PFM, Meacock SE, Lambert JM (1976) Investigations into the properties of quantitative vegetational data: II. Further data type comparisons. Journal of Ecology 64, 41–78.
| Investigations into the properties of quantitative vegetational data: II. Further data type comparisons.Crossref | GoogleScholarGoogle Scholar |
Specht RL (1981) Foliage projective cover and standing biomass. In ‘Vegetation Classification in Australia’. (Eds AN Gillison, DJ Anderson) pp. 10–21. (CSIRO in association with Australian National University Press: Canberra)
Stanton JP, Morgan MG (1977) Project RAKES – The rapid selection and appraisal of key and endangered sites: the Queensland case study. PR 4. (Department of Environment, Housing and Community Development, University of New England: Armidale, NSW, Australia)
Stromberg JC, Merritt DM (2016) Riparian plant guilds of ephemeral, intermittent and perennial rivers. Freshwater Biology 61, 1259–1275.
| Riparian plant guilds of ephemeral, intermittent and perennial rivers.Crossref | GoogleScholarGoogle Scholar |
Thackway R, Cresswell ID (1995) ‘An interim Biogeographic Regionalisation for Australia: a Framework for Establishing the National System of Reserves. Ver. 4.0.’ (Australian Nature Conservation Agency: Canberra)
Tichý L, Chytrý M, Hajek M, Talbot SS, Botta-Dukát Z (2010) OptimClass: using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities. Journal of Vegetation Science 21, 287–299.
| OptimClass: using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities.Crossref | GoogleScholarGoogle Scholar |
Tichý L, Chytrý M, Botta-Dukát Z (2014) Semi-supervised classification of vegetation: preserving the good old units and searching for new ones. Journal of Vegetation Science 25, 1504–1512.
| Semi-supervised classification of vegetation: preserving the good old units and searching for new ones.Crossref | GoogleScholarGoogle Scholar |
Tichý L, Hennekens SM, Novák P, Rodwell JS, Schaminée JHJ, Chytrý M (2020) Optimal transformation of species cover for vegetation classification. Applied Vegetation Science 23, 710–717.
| Optimal transformation of species cover for vegetation classification.Crossref | GoogleScholarGoogle Scholar |
Walker DA, Daniels FJA, Matveyeva NV, Sibik J, Walker MD, Breen AL, Druckenmiller LA, Raynolds MK, Bultmann H, Hennekens S, Buchhorn M, Epstein HE, Ermokhina K, Fosaa AM, Heidmarsson S, Heim B, Jonsdottir IS, Koroleva N, Levesque E, MacKenzie WH, Henry GHR, Nilsen L, Peet R, Razzhivin V, Talbot SS, Telyatnikov M, Thannheiser D, Webber PJ, Wirth LM (2018) Circumpolar Arctic vegetation classification. Phytocoenologia 48, 181–201.
| Circumpolar Arctic vegetation classification.Crossref | GoogleScholarGoogle Scholar |
Wesche K, von Wehrden H (2011) Surveying southern Mongolia: application of multivariate classification methods in drylands with low diversity and long floristic gradients. Applied Vegetation Science 14, 561–570.
| Surveying southern Mongolia: application of multivariate classification methods in drylands with low diversity and long floristic gradients.Crossref | GoogleScholarGoogle Scholar |
Whittaker RH (1973) Approaches to classifying vegetation. In ‘Ordination and Classification of Communities’. (Ed. RH Whittaker) pp. 323–354. (Junk: The Hague, Netherlands).
Wilson PR, Taylor PM (2012) Land zones of Queensland. Available at http://www.ehp.qld.gov.au/assets/documents/plants-animals/ecosystems/land-zones-queensland.pdf. [Verified 15 August 2020]
Wiser SK, De Cáceres M (2013) Updating vegetation classifications: an example with New Zealand’s woody vegetation. Journal of Vegetation Science 24, 80–93.
| Updating vegetation classifications: an example with New Zealand’s woody vegetation.Crossref | GoogleScholarGoogle Scholar |
Wiser SK, De Cáceres M (2018) New Zealand’s plot-based classification of vegetation. Phytocoenologia 48, 153–161.
| New Zealand’s plot-based classification of vegetation.Crossref | GoogleScholarGoogle Scholar |
