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Australian Journal of Botany Australian Journal of Botany Society
Southern hemisphere botanical ecosystems
RESEARCH ARTICLE

Vegetation change along a Mediterranean to arid zone bioclimatic gradient reveals scale-dependent ecotone patterning

S. Caddy-Retalic https://orcid.org/0000-0003-4870-4202 A B D , G. M. Wardle B , E. J. Leitch A , F. A. McInerney C and A. J. Lowe A
+ Author Affiliations
- Author Affiliations

A School of Biological Sciences and Environment Institute, University of Adelaide, North Terrace, SA 5005, Australia.

B School of Life and Environmental Sciences, University of Sydney, Sydney, NSW 2006, Australia.

C School of Physical Sciences and Sprigg Geobiology Centre, University of Adelaide, North Terrace, SA 5005, Australia.

D Corresponding author. Email: stefan.caddy-retalic@adelaide.edu.au

Australian Journal of Botany 68(8) 574-586 https://doi.org/10.1071/BT20036
Submitted: 3 April 2020  Accepted: 26 October 2020   Published: 4 December 2020

Abstract

The drivers and rate of vegetation change across spatial gradients can give critical insights into the compositional and structural change we can expect under climate change. Spatial ecotones are of particular interest as they represent heterogeneity in the patterning of vegetation that may reflect how temporal environmental change will manifest in more abrupt step changes in plant composition and/or structure. Another dimension of interest is the degree to which survey methodology impacts the detectability of thresholds in vegetation. We surveyed a Mediterranean to arid zone gradient in South Australia with nested and non-nested transect designs and related the observed vegetation change to soil, landscape and climate to determine the strongest environmental associations. Ordination, principal components analysis (PCA) and threshold indicator taxa analysis (TITAN) were used to detect potential ecotones associated with environmental thresholds. Results from the two transects were compared with test the effects of survey method and spatial sampling on pattern detection. Ordinations and regressions for both transects indicated vegetation changed linearly along the environmental gradient. Species richness and total cover increased with rainfall. Species turnover was very high, with low nestedness, indicating high susceptibility to environmental change. Climate is the major driver of broad-scale vegetation change on our gradient and at this scale vegetation trends are detectable with a range of survey methodologies. TITAN identification of a threshold within the shorter, nested transect (but not the longer transect which extended into the arid zone) indicated that survey methodology influences ecotone detectability, and that although smaller-scale vegetation disjunctions may be present, change spanning the entire mesic to arid zone is largely monotonic.

Keywords: climate change impacts, complex gradients, ecotone, heterogeneity, Mediterranean biome, nestedness, ordination, PCA, plant composition, survey methodology, TITAN, transects, vegetation gradients.


References

Abbott IAN, Le Maitre D (2010) Monitoring the impact of climate change on biodiversity: the challenge of megadiverse Mediterranean climate ecosystems. Austral Ecology 35, 406–422.

Allen CD, Breshears DD (1998) Drought-induced shift of a forest–woodland ecotone: rapid landscape response to climate variation. Proceedings of the National Academy of Sciences of the United States of America 95, 14839–14842.

Aronson J, Shmida A (1992) Plant species diversity along a Mediterranean-desert gradient and its correlation with interannual rainfall fluctuations. Journal of Arid Environments 23, 235–247.
Plant species diversity along a Mediterranean-desert gradient and its correlation with interannual rainfall fluctuations.Crossref | GoogleScholarGoogle Scholar |

Auerbach M, Shmida A (1993) Vegetation change along an altitudinal gradient on Mt Hermon, Israel – no evidence for discrete communities. Journal of Ecology 81, 25–33.
Vegetation change along an altitudinal gradient on Mt Hermon, Israel – no evidence for discrete communities.Crossref | GoogleScholarGoogle Scholar |

Austin MP (1999) The potential contribution of vegetation ecology to biodiversity research. Ecography 22, 465–484.
The potential contribution of vegetation ecology to biodiversity research.Crossref | GoogleScholarGoogle Scholar |

Baker ME, King RS (2010) A new method for detecting and interpreting biodiversity and ecological community thresholds. Methods in Ecology and Evolution 1, 25–37.
A new method for detecting and interpreting biodiversity and ecological community thresholds.Crossref | GoogleScholarGoogle Scholar |

Baker ME, King RS, Kahle D (2019) ‘TITAN2: Threshold Indicator Taxa Analysis. R package version 2.4.’ Available at https://CRAN.R-project.org/package=TITAN2

Barker W, Barker R, Jessop J, Vonow H (2016) ‘Census of South Australian plants, Algae and fungi.’ (State Herbarium of South Australia: Adelaide, SA, Australia)

Baselga A, Orme CDL (2012) betapart: an R package for the study of beta diversity. Methods in Ecology and Evolution 3, 808–812.
betapart: an R package for the study of beta diversity.Crossref | GoogleScholarGoogle Scholar |

Bhattarai KR, Vetaas OR (2003) Variation in plant species richness of different life forms along a subtropical elevation gradient in the Himalayas, east Nepal. Global Ecology and Biogeography 12, 327–340.
Variation in plant species richness of different life forms along a subtropical elevation gradient in the Himalayas, east Nepal.Crossref | GoogleScholarGoogle Scholar |

Blois JL, Williams JW, Fitzpatrick MC, Jackson ST, Ferrier S (2013) Space can substitute for time in predicting climate-change effects on biodiversity. Proceedings of the National Academy of Sciences of the United States of America 110, 9374–9379.
Space can substitute for time in predicting climate-change effects on biodiversity.Crossref | GoogleScholarGoogle Scholar | 23690569PubMed |

Bonham CD (2013) ‘Measurements for terrestrial vegetation.’ (Wiley Online Library)

Bråkenhielm S, Qinghong L (1995) Comparison of field methods in vegetation monitoring. In ‘Biogeochemical monitoring in small catchments’. (Eds J Černý, M. Novák, T. Pačes, RK Wieder) pp. 75–87. (Springer: Berlin)

Buckley LB, Jetz W (2008) Linking global turnover of species and environments. Proceedings of the National Academy of Sciences of the United States of America 105, 17836–17841.
Linking global turnover of species and environments.Crossref | GoogleScholarGoogle Scholar | 19001274PubMed |

Caddy-Retalic S, Andersen AN, Aspinwall MJ, Breed MF, Byrne M, Christmas MJ, Dong N, Evans BJ, Fordham DA, Guerin GR, Hoffmann AA, Hughes AC, van Leeuwen SJ, McInerney FA, Prober SM, Rossetto M, Rymer PD, Steane DA, Wardle GM, Lowe AJ (2017) Bioclimatic transect networks: powerful observatories of ecological change. Ecology and Evolution 7, 4607–4619.
Bioclimatic transect networks: powerful observatories of ecological change.Crossref | GoogleScholarGoogle Scholar | 28690791PubMed |

Caddy-Retalic S, Leitch EJ, Wardle GM, Lowe AJ (2018) An overview of the TREND Technical Report. Available at http://www.ausplots.org/s/An-overview-of-the-TREND_Caddy-Retalic-etc-al.pdf

Callaway RM, Walker LR (1997) Competition and facilitation: a synthetic approach to interactions in plant communities. Ecology 78, 1958–1965.
Competition and facilitation: a synthetic approach to interactions in plant communities.Crossref | GoogleScholarGoogle Scholar |

Conover DO, Schultz ET (1995) Phenotypic similarity and the evolutionary significance of countergradient variation. Trends in Ecology & Evolution 10, 248–252.
Phenotypic similarity and the evolutionary significance of countergradient variation.Crossref | GoogleScholarGoogle Scholar |

Cowling RM, Rundel PW, Lamont BB, Kalin Arroyo M, Arianoutsou M (1996) Plant diversity in mediterranean-climate regions. Trends in Ecology & Evolution 11, 362–366.
Plant diversity in mediterranean-climate regions.Crossref | GoogleScholarGoogle Scholar |

Crausbay SD, Hotchkiss SC (2010) Strong relationships between vegetation and two perpendicular climate gradients high on a tropical mountain in Hawai’i. Journal of Biogeography 37, 1160–1174.
Strong relationships between vegetation and two perpendicular climate gradients high on a tropical mountain in Hawai’i.Crossref | GoogleScholarGoogle Scholar |

De Frenne P, Graae BJ, Rodríguez-Sánchez F, Kolb A, Chabrerie O, Decoq G, De Kort H, De Schrijver A, Diekmann M, Eriksson O, Gruwez R, Hermy M, Lenoir J, Plue J, Coomes DA, Verheyen K (2013) Latitudinal gradients as natural laboratories to infer species’ responses to temperature. Journal of Ecology 101, 784–795.
Latitudinal gradients as natural laboratories to infer species’ responses to temperature.Crossref | GoogleScholarGoogle Scholar |

Díaz-Varela RA, Colombo R, Meroni M, Calvo-Iglesias MS, Buffoni A, Tagliaferri A (2010) Spatio-temporal analysis of alpine ecotones: a spatial explicit model targeting altitudinal vegetation shifts. Ecological Modelling 221, 621–633.
Spatio-temporal analysis of alpine ecotones: a spatial explicit model targeting altitudinal vegetation shifts.Crossref | GoogleScholarGoogle Scholar |

Dickman C, Wardle G, Foulkes J, de Preu N (2014) Desert complex environments. In ‘Biodiversity and environmental change: monitoring, challenges and direction’. (Eds D Lindenmayer, E Burns, N Thurgate, A Lowe) pp. 379–438. (CSIRO Publishing: Collingwood, Victoria)

Flores J, Jurado E, Ezcurra E (2003) Are nurse-protégé interactions more common among plants from arid environments? Journal of Vegetation Science 14, 911–916.
Are nurse-protégé interactions more common among plants from arid environments?Crossref | GoogleScholarGoogle Scholar |

Gibson N, Prober S, Meissner R, van Leeuwen S (2017) Implications of high species turnover on the south-western Australian sandplains. PLoS One 12, e0172977
Implications of high species turnover on the south-western Australian sandplains.Crossref | GoogleScholarGoogle Scholar | 28245232PubMed |

Guerin GR, Biffin E, Lowe AJ (2013) Spatial modelling of species turnover identifies climate ecotones, climate change tipping points and vulnerable taxonomic groups. Ecography 36, 1086–1096.
Spatial modelling of species turnover identifies climate ecotones, climate change tipping points and vulnerable taxonomic groups.Crossref | GoogleScholarGoogle Scholar |

Guerin GR, Biffin E, Jardine DI, Cross HB, Lowe AJ (2014) A spatially predictive baseline for monitoring multivariate species occurrences and phylogenetic shifts in mediterranean southern Australia. Journal of Vegetation Science 25, 338–348.
A spatially predictive baseline for monitoring multivariate species occurrences and phylogenetic shifts in mediterranean southern Australia.Crossref | GoogleScholarGoogle Scholar |

Guerin GR, Biffin E, Jardine DI, Cross HB, Lowe AJ (2015) TREND (PSRF) vegetation plot data 2011. Australian Ecological Knowledge and Observation System data portal.

Guerin GR, Sweeney SM, Pisanu P, Caddy-Retalic S, Lowe AJ (2016) Establishment of an ecosystem transect to address climate change policy questions for natural resource management. DEWNR Technical Report. South Australian Department of Environment, Water and Natural Resources, Adelaide, SA, Australia.

Halbritter AH, Fior S, Keller I, Billeter R, Edwards PJ, Holderegger R, Karrenberg S, Pluess AR, Widmer A, Alexander JM (2018) Trait differentiation and adaptation of plants along elevation gradients. Journal of Evolutionary Biology 31, 784–800.
Trait differentiation and adaptation of plants along elevation gradients.Crossref | GoogleScholarGoogle Scholar | 29518274PubMed |

Hutchinson MF, McIntyre S, Hobbs RJ, Stein JL, Garnett S, Kinloch J (2005) Integrating a global agro-climatic classification with bioregional boundaries in Australia. Global Ecology and Biogeography 14, 197–212.
Integrating a global agro-climatic classification with bioregional boundaries in Australia.Crossref | GoogleScholarGoogle Scholar |

Kapfer J, Hédl R, Jurasinski G, Kopecký M, Schei FH, Grytnes JA (2016) Resurveying historical vegetation data–opportunities and challenges. Applied Vegetation Science 20, 164–171.
Resurveying historical vegetation data–opportunities and challenges.Crossref | GoogleScholarGoogle Scholar | 30245580PubMed |

Kennedy K, Addison P (1987) Some considerations for the use of visual estimates of plant cover in biomonitoring. Journal of Ecology 75, 151–157.
Some considerations for the use of visual estimates of plant cover in biomonitoring.Crossref | GoogleScholarGoogle Scholar |

Klausmeyer KR, Shaw MR (2009) Climate change, habitat loss, protected areas and the climate adaptation potential of species in mediterranean ecosystems worldwide. PLoS One 4, e6392
Climate change, habitat loss, protected areas and the climate adaptation potential of species in mediterranean ecosystems worldwide.Crossref | GoogleScholarGoogle Scholar | 19641600PubMed |

Kreyling J, Jentsch A, Beier C (2014) Beyond realism in climate change experiments: gradient approaches identify thresholds and tipping points. Ecology Letters 17, 125
Beyond realism in climate change experiments: gradient approaches identify thresholds and tipping points.Crossref | GoogleScholarGoogle Scholar | 24341985PubMed |

Kutiel P, Lavee H, Shoshany M (1995) Influence of a climatic gradient upon vegetation dynamics along a Mediterranean-arid transect. Journal of Biogeography 22, 1065–1071.
Influence of a climatic gradient upon vegetation dynamics along a Mediterranean-arid transect.Crossref | GoogleScholarGoogle Scholar |

Lenton TM (2011) Early warning of climate tipping points. Nature Climate Change 1, 201–209.
Early warning of climate tipping points.Crossref | GoogleScholarGoogle Scholar |

Lepš J, Hadincová V (1992) How reliable are our vegetation analyses? Journal of Vegetation Science 3, 119–124.
How reliable are our vegetation analyses?Crossref | GoogleScholarGoogle Scholar |

Maestre FT, Callaway RM, Valladares F, Lortie CJ (2009) Refining the stress‐gradient hypothesis for competition and facilitation in plant communities. Journal of Ecology 97, 199–205.
Refining the stress‐gradient hypothesis for competition and facilitation in plant communities.Crossref | GoogleScholarGoogle Scholar |

Marra GP, Wood SN (2011) Practical variable selection for generalized additive models. Computational Statistics & Data Analysis 55, 2372–2387.
Practical variable selection for generalized additive models.Crossref | GoogleScholarGoogle Scholar |

McDonald RC, Isbell RF (2009) ‘Soil profile In Australian soil and land survey field handbook’, 3rd edn. (CSIRO Publishing: Melbourne, Vic., Australia)

Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2019) vegan: Community Ecology Package. R package version 2.5-6. Available at https://CRAN.R-project.org/package=vegan

Otypková Z, Chytrý M, Kenkel N (2006) Effects of plot size on the ordination of vegetation samples. Journal of Vegetation Science 17, 465–472.
Effects of plot size on the ordination of vegetation samples.Crossref | GoogleScholarGoogle Scholar |

Palmer MW (1993) Putting things in even better order: the advantages of canonical correspondence analysis. Ecology 74, 2215–2230.
Putting things in even better order: the advantages of canonical correspondence analysis.Crossref | GoogleScholarGoogle Scholar |

Pausas JG, Austin MP (2001) Patterns of plant species richness in relation to different environments: an appraisal. Journal of Vegetation Science 12, 153–166.
Patterns of plant species richness in relation to different environments: an appraisal.Crossref | GoogleScholarGoogle Scholar |

Powers RF, Reynolds PE (1999) Ten-year responses of ponderosa pine plantations to repeated vegetation and nutrient control along an environmental gradient. Canadian Journal of Forest Research 29, 1027–1038.
Ten-year responses of ponderosa pine plantations to repeated vegetation and nutrient control along an environmental gradient.Crossref | GoogleScholarGoogle Scholar |

R Core Team (2017) R: a language and environment for statistical computing. (R Foundation for Statistical Computing: Vienna, Austria) Available at http://www.r-project.org [Verified 30 October 2020]

Siefert A, Ravenscroft C, Althoff D, Alvarez-Yépiz JC, Carter BE, Glennon KL, Heberling JM, Jo IS, Pontes A, Sauer A, Willis A, Fridley JD (2012) Scale dependence of vegetation–environment relationships: a meta-analysis of multivariate data. Journal of Vegetation Science 23, 942–951.
Scale dependence of vegetation–environment relationships: a meta-analysis of multivariate data.Crossref | GoogleScholarGoogle Scholar |

Soininen J (2010) Species turnover along abiotic and biotic gradients: patterns in space equal patterns in time? Bioscience 60, 433–439.
Species turnover along abiotic and biotic gradients: patterns in space equal patterns in time?Crossref | GoogleScholarGoogle Scholar |

Soliveres S, Eldridge DJ, Hemmings F (2012) Nurse plant effects on plant species richness in drylands: the role of grazing, rainfall and species specificity. Perspectives in Plant Ecology, Evolution and Systematics 14, 402–410.
Nurse plant effects on plant species richness in drylands: the role of grazing, rainfall and species specificity.Crossref | GoogleScholarGoogle Scholar | 25914602PubMed |

Sparrow B, Foulkes J, Wardle G, Leitch E, Caddy-Retalic S, van Leeuwen S, Tokmakoff A, Thurgate N, Guerin GR, Lowe AJ (2020) A vegetation and soil survey method for surveillance monitoring of rangeland environments. Frontiers in Ecology and Evolution 8, 157
A vegetation and soil survey method for surveillance monitoring of rangeland environments.Crossref | GoogleScholarGoogle Scholar |

Tierney DA, Wardle GM, Erskine PD (2018) The intersection of diversity metrics and spatial mapping: a case study of regional vegetation patterns for a complex community. Plant Ecology 219, 1169–1183.
The intersection of diversity metrics and spatial mapping: a case study of regional vegetation patterns for a complex community.Crossref | GoogleScholarGoogle Scholar |

Underwood EC, Viers JH, Klausmeyer KR, Cox RL, Shaw MR (2009) Threats and biodiversity in the mediterranean biome. Diversity & Distributions 15, 188–197.
Threats and biodiversity in the mediterranean biome.Crossref | GoogleScholarGoogle Scholar |

Vanha-Majamaa I, Salemaa M, Tuominen S, Mikkola K (2000) Digitized photographs in vegetation analysis – a comparison of cover estimates. Applied Vegetation Science 3, 89–94.
Digitized photographs in vegetation analysis – a comparison of cover estimates.Crossref | GoogleScholarGoogle Scholar |

Vittoz P, Guisan A (2007) How reliable is the monitoring of permanent vegetation plots? A test with multiple observers. Journal of Vegetation Science 18, 413–422.
How reliable is the monitoring of permanent vegetation plots? A test with multiple observers.Crossref | GoogleScholarGoogle Scholar |

Warren DL, Cardillo M, Rosauer DF, Bolnick DI (2014) Mistaking geography for biology: inferring processes from species distributions. Trends in Ecology & Evolution 29, 572–580.
Mistaking geography for biology: inferring processes from species distributions.Crossref | GoogleScholarGoogle Scholar |

White A, Sparrow B, Leitch E, Foulkes J, Flitton R, Lowe A, Caddy-Retalic S (2012) ‘AusPlots rangelands survey protocols manual, ver. 1.2.9.’ (University of Adelaide Press: Adelaide, SA, Australia)

Williams KJ, Belbin L, Austin MP, Stein JL, Ferrier S (2012) Which environmental variables should I use in my biodiversity model? International Journal of Geographical Information Science 26, 2009–2047.
Which environmental variables should I use in my biodiversity model?Crossref | GoogleScholarGoogle Scholar |

Zimmerman AS (2008) New knowledge from old data the role of standards in the sharing and reuse of ecological data. Science, Technology & Human Values 33, 631–652.
New knowledge from old data the role of standards in the sharing and reuse of ecological data.Crossref | GoogleScholarGoogle Scholar |