Towards a statistically robust determination of minimum water potential and hydraulic risk in plants
| Autor: | Louis S. Santiago, Alberto Vilagrosa, Miquel De Cáceres, Maurizio Mencuccini, Ismael Aranda, Jordi Martínez-Vilalta, Rafael Poyatos, Sylvain Delzon, Llorenç Badiella |
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| Přispěvatelé: | Universidad de Alicante. Departamento de Ecología, CEAM (Centro de Estudios Ambientales del Mediterráneo), Gestión de Ecosistemas y de la Biodiversidad (GEB), Ministerio de Ciencia e Innovación (España), Martinez-Vilalta, J, Santiago, LS, Poyatos, R, Badiella, L, de Caceres, M, Aranda, I, Delzon, S, Vilagrosa, A, Mencuccini, M, Martinez-Vilalta, J [0000-0002-2332-7298], Santiago, LS [0000-0001-5994-6122], Poyatos, R [0000-0003-0521-2523], Badiella, L [0000-0002-9653-7421], de Caceres, M [0000-0001-7132-2080], Aranda, I [0000-0001-9086-7940], Delzon, S [0000-0003-3442-1711], Vilagrosa, A [0000-0002-1432-1214], Mencuccini, M [0000-0003-0840-1477] |
| Rok vydání: | 2021 |
| Předmět: |
Resistance (ecology)
Droughttolerance Extreme values Physiology Water Hydraulic risk Minimum water potential Sampling (statistics) Sample (statistics) Drought resistance Plant Science Drought tolerance Ecología Representativeness heuristic Plant Leaves Variable (computer science) Minimum waterpotential Hydraulic safety margin Xylem Sample size determination Statistics Environmental science Probability distribution Physiological limits Extreme value theory |
| Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 1469-8137 0028-646X |
| Popis: | Centro de Investigación Forestal (CIFOR) Minimum water potential (Ψmin ) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution. We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk. Our results show that current estimates of Ψmin and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species. Although data availability and representativeness remain the main challenges for proper determination of Ψmin , a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks. This research was supported by the Spanish Ministry of Scienceand Innovation (MICINN) via competitive grants CGL2017-89149-C2-1-R and CGL2017-89149-C2-2-R. AV thanksMICINN for the project Inertia (PID201-111332RB-C22). JM-V benefited from an ICREA Academia award. We want to thankSanna Sevanto, Nate McDowell and co-authors for making theSUMO water potential data publicly available (https://doi.org/10.15485/1439886). |
| Databáze: | OpenAIRE |
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