Dead or Alive? Using Membrane Failure and Chlorophyll a Fluorescence to Predict Plant Mortality from Drought.
Plant Physiol
; 175(1): 223-234, 2017 Sep.
Article
em En
| MEDLINE
| ID: mdl-28710130
ABSTRACT
Climate models predict widespread increases in both drought intensity and duration in the next decades. Although water deficiency is a significant determinant of plant survival, limited understanding of plant responses to extreme drought impedes forecasts of both forest and crop productivity under increasing aridity. Drought induces a suite of physiological responses; however, we lack an accurate mechanistic description of plant response to lethal drought that would improve predictive understanding of mortality under altered climate conditions. Here, proxies for leaf cellular damage, chlorophyll a fluorescence, and electrolyte leakage were directly associated with failure to recover from drought upon rewatering in Brassicarapa (genotype R500) and thus define the exact timing of drought-induced death. We validated our results using a second genotype (imb211) that differs substantially in life history traits. Our study demonstrates that whereas changes in carbon dynamics and water transport are critical indicators of drought stress, they can be unrelated to visible metrics of mortality, i.e. lack of meristematic activity and regrowth. In contrast, membrane failure at the cellular scale is the most proximate cause of death. This hypothesis was corroborated in two gymnosperms (Picea engelmannii and Pinus contorta) that experienced lethal water stress in the field and in laboratory conditions. We suggest that measurement of chlorophyll a fluorescence can be used to operationally define plant death arising from drought, and improved plant characterization can enhance surface model predictions of drought mortality and its consequences to ecosystem services at a global scale.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Membrana Celular
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Clorofila
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Brassica rapa
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Secas
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Fluorometria
Tipo de estudo:
Evaluation_studies
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Prognostic_studies
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Risk_factors_studies
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article