Response of seagrass indicators to shifts in environmental stressors: A global review and management synthesis

Although seagrass-based indicators are widely used to assess coastal ecosystem status, there is little universality in their application. Matching the plethora of available indicators to specific management objectives requires a detailed knowledge of their species-specific sensitivities and their re...

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Bibliographic Details
Published in:Ecological indicators 2016-04, Vol.63, p.310-323
Main Authors: Roca, G., Alcoverro, T., Krause-Jensen, D., Balsby, T.J.S., van Katwijk, M.M., Marbà, N., Santos, R., Arthur, R., Mascaró, O., Fernández-Torquemada, Y., Pérez, M., Duarte, C.M., Romero, J.
Format: Article
Language:English
Subjects:
biomass
Coastal assessment
decision support systems
Decision trees
Degradació ambiental
Degradation
Density
Early warning indicators
Ecosystem degradation
Ecosystems
Environmental degradation
Environmental policy
Estrès (Fisiologia)
Flora marina
Indicators
Management
managers
Marine plants
Physiological and indicators
Política ambiental
Recovery
Response time
Seagrass recovery
seagrasses
Stress (Physiology)
surveys
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Summary:Although seagrass-based indicators are widely used to assess coastal ecosystem status, there is little universality in their application. Matching the plethora of available indicators to specific management objectives requires a detailed knowledge of their species-specific sensitivities and their response time to environmental stressors. We conducted an extensive survey of experimental studies to determine the sensitivity and response time of seagrass indicators to ecosystem degradation and recovery. We identified seagrass size and indicator type (i.e. level of biological organization of the measure) as the main factors affecting indicator sensitivity and response time to degradation and recovery. While structural and demographic parameters (e.g. shoot density, biomass) show a high and unspecific sensitivity, biochemical/physiological indicators present more stressor-specific responses and are the most sensitive detecting early phases of environmental improvement. Based on these results we present a simple decision tree to assist ecosystem managers to match adequate and reliable indicators to specific management goals.
ISSN:1470-160X
1872-7034
DOI:10.1016/j.ecolind.2015.12.007