From field uncertainty to ecological status: how indicator architecture propagates observational variability
Abstract
Ecological assessments based on biological communities rely on the implicit assumption that field observations provide a sufficiently robust description of communities to support reliable ecological diagnoses. Although numerous studies have investigated indicator performance or the different sources of uncertainty associated with biological monitoring, the waythis uncertainty propagates through the assessment process to ecological classifications remains poorly documented. This issue arises within the framework of the European Water Framework Directive (WFD), where macrophytes are considered as a biological quality element to assess the ecological status of Mediterranean poly-euhaline lagoons. The present study investigates the propagation of inter-operator variability throughout the ecological assessment process. Ten experienced operators independently applied the field protocol at four monitoring sites in the Thau lagoon in France. Each independent description of the macrophyte communities was subsequently used as a common basis for calculating three European intercalibrated indicators (The Ecological Evaluation Index (EEI), the Expert-Macrophyte Quality Index (E-MaQI), and the EXamination tool for Coastal Lagoon Macrophyte Ecological status (EXCLAME). This allowed to examine how the same community description was interpreted by different indicators and translated into ecological diagnoses. The observed variability depended not only on the operators but also on the characteristics of the communities being surveyed. The results further demonstrated that this variability was not propagated uniformly across indicators, whose architectures, biological variables, aggregation rules, and calculation procedures differentially modulate the consequences of field observations on ecological assessments. Beyond quantifying inter-operator variability, this study shows that the robustness of ecological assessments depends similarly on the production of ecological information in the field and on its translation into ecological diagnoses. These findings highlight the need to better characterize the uncertainty associated with biological observations and suggest that complementary observation approaches, including image-based and molecular methods, may enrich community descriptions and strengthen the robustness of ecological assessments.
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BibTeX
@misc{cimiterra2026from,
title = {{From field uncertainty to ecological status: how indicator architecture propagates observational variability}},
author = {Nicolas Cimiterra and Vincent Ouisse and Angélique Gobet and Valérie Derolez and Thierry Laugier},
howpublished = {HAL},
year = {2026},
month = oct,
url = {https://hal.science/hal-05829734v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - From field uncertainty to ecological status: how indicator architecture propagates observational variability
AU - Nicolas Cimiterra
AU - Vincent Ouisse
AU - Angélique Gobet
AU - Valérie Derolez
AU - Thierry Laugier
PY - 2026
DA - 2026/10/21
PB - HAL
UR - https://hal.science/hal-05829734v1
AB - Ecological assessments based on biological communities rely on the implicit assumption that field observations provide a sufficiently robust description of communities to support reliable ecological diagnoses. Although numerous studies have investigated indicator performance or the different sources of uncertainty associated with biological monitoring, the waythis uncertainty propagates through the assessment process to ecological classifications remains poorly documented. This issue arises within the framework of the European Water Framework Directive (WFD), where macrophytes are considered as a biological quality element to assess the ecological status of Mediterranean poly-euhaline lagoons. The present study investigates the propagation of inter-operator variability throughout the ecological assessment process. Ten experienced operators independently applied the field protocol at four monitoring sites in the Thau lagoon in France. Each independent description of the macrophyte communities was subsequently used as a common basis for calculating three European intercalibrated indicators (The Ecological Evaluation Index (EEI), the Expert-Macrophyte Quality Index (E-MaQI), and the EXamination tool for Coastal Lagoon Macrophyte Ecological status (EXCLAME). This allowed to examine how the same community description was interpreted by different indicators and translated into ecological diagnoses. The observed variability depended not only on the operators but also on the characteristics of the communities being surveyed. The results further demonstrated that this variability was not propagated uniformly across indicators, whose architectures, biological variables, aggregation rules, and calculation procedures differentially modulate the consequences of field observations on ecological assessments. Beyond quantifying inter-operator variability, this study shows that the robustness of ecological assessments depends similarly on the production of ecological information in the field and on its translation into ecological diagnoses. These findings highlight the need to better characterize the uncertainty associated with biological observations and suggest that complementary observation approaches, including image-based and molecular methods, may enrich community descriptions and strengthen the robustness of ecological assessments.
ER -