Published June 20, 2023 | Version v1
Dataset Open

Compositional shifts of alpine plant communities across the High Andes

  • 1. Universidad de las Américas
  • 2. Royal Botanic Gardens
  • 3. National University of Tucumán
  • 4. Consortium for Sustainable Development of the Andean Ecoregion
  • 5. Pontificia Universidad Católica del Ecuador
  • 6. National Scientific and Technical Research Council
  • 7. Catholic University of the North
  • 8. University of Miami
  • 9. Austrian Academy of Sciences
  • 10. Universidad Nacional de Loja
  • 11. Museo Nacional de Historia Natural*
  • 12. The University of Texas at Austin
  • 13. Universidad de Los Andes
  • 14. Ministry for Primary Industries
  • 15. National Agricultural Technology Institute
  • 16. Stony Brook University

Description

Aim: Climate change is transforming mountain summit plant communities worldwide, but we know little about such changes in the High Andes. Understanding large-scale patterns of vegetation changes across the Andes, and the factors driving these changes, is fundamental to predicting the effects of global warming. We assessed trends in vegetation cover, species richness (SR) and community-level thermal niches (CTN) and tested whether they are explained by summits' climatic conditions and soil temperature trends.

Location: High Andes

Time period: Between 2011/2012 and 2017/2019

Major taxa studied: Vascular plants

Methods: Using permanent vegetation plots placed on 45 mountain summits and soil temperature loggers situated along a ~6,800 km N-S gradient, we measured species and their percentage cover and estimated CTN in two surveys (intervals between 5-8 years). We then estimated the annual rate of changes for the three variables and used generalized linear models to assess their relationship with rates of change in the locally recorded soil temperatures, annual precipitation, and the minimum air temperatures of each summit.

Results: Over time, there was an average loss of vegetation cover (mean = -0.26 %/yr), and a gain in SR across summits (mean = 0.38 species m2/yr), but most summits had significant increases in SR and vegetation cover. Changes in SR were positively related to minimum air temperature and soil temperature rate of change. Most plant communities experienced shifts in their composition by including greater abundances of species with broader thermal niches and higher optima. However, the measured changes in soil temperature did not explain the observed changes in CTN.

Main conclusions: High-Andean vegetation is changing in cover and SR and is shifting towards species with wider thermal niche breadths. The weak relationship with soil temperature trends could have resulted from the short study period that only marginally captures changes in vegetation through time.

Notes

(1) R-studio; (2) QGis

For further information, users are advised to refer to the README document ("README_Dataset-compositional-changes_Andes.md") and the accompanying published article: Cuesta, F., Carilla, J., LLambí, L.D., Muriel, P., Lencinas, M. V., Meneses R.I., Feeley, K., Pauli, H., Aguirre, N., Beck, S., Bernardi, A., Cuello, Duchicela, S. A., Eguiguren, P., Gamez, L.E., Halloy, S., Hudson, L., Jaramillo, R., Peri, P.L., Ramírez, L. A., Rosero-Añazco, P., Thompson N., Yager, K., Tovar, C.  Compositional shifts of alpine plant communities across the high Andes. Global Ecology and Biogeography. Accepted. DOI: 10.1111/geb.13721  

Funding provided by: Universidad de Las Américas Ecuador
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100021068
Award Number: FGE.FCC.20.01

Funding provided by: Direktion für Entwicklung und Zusammenarbeit
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100009131
Award Number: 81028631

Funding provided by: Direktion für Entwicklung und Zusammenarbeit
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100009131
Award Number: 81062762

Files

annual_changes_cov_richness_by_biog_biome.csv

Files (6.0 MB)

Name Size Download all
md5:d53964f9283ad9cecae4a42d6f7d74a0
3.3 kB Download
md5:a051094e2cc11688f9fee2de9e11fd50
7.8 kB Download
md5:477cbca6611e85a1b68ae2fe63dcde8a
2.0 kB Download
md5:7fb748d4e660286b7522221236382d68
2.8 kB Download
md5:b0319eae3b0f14ad24000c40dc7f65cd
4.1 kB Download
md5:b4dc89f8137acbe9a6980c5b8b470668
2.5 kB Download
md5:19264d902e7db135e09ad7482e81244e
2.5 kB Preview Download
md5:ffa637c5942d309803fce324ea42e2cb
3.2 kB Preview Download
md5:8dcfe54e0e0170729df173b63bab0c17
7.8 kB Preview Download
md5:86f589684c7947452bd0cdd0260a33ef
922 Bytes Preview Download
md5:3af9867d07cc96d664053a3e8bdf0b10
5.8 MB Preview Download
md5:f4906fd9ae683687b66dcb70a34ba1c6
18.1 kB Preview Download
md5:3e5ad39b538adf030ad0def8625b81bc
58 Bytes Preview Download
md5:30af348d89fb3d7a5b65d53f31d5221f
5.0 kB Preview Download
md5:78b74db184d1ad3f2f9b034b545b8328
127.4 kB Preview Download
md5:35009458b2d82a35687aa53a6d3a00aa
8.3 kB Preview Download
md5:9dfe16f182347243e679afbb120147c9
75 Bytes Preview Download
md5:e76b77dd6506a3bbbbe94c6101448af3
60 Bytes Preview Download