@article{fdi:010096926,
  title = {{F}rom calibration to identifiability analysis : using a multi-reserve {DEB} model to understand holopelagic {S}argassum spp. growth},
  author = {{L}agunes, {M}. {J}. and {M}arques, {G}. {M}. and {S}alas-{A}costa, {E}. {R}. and {V}ásquez-{E}lizondo, {R}. {M}. and {T}hibaut, {T}. and {R}obledo, {D}. and {C}onnan, {S}. and {S}tiger-{P}ouvreau, {V}. and {B}erline, {L}. and {L}ett, {C}hristophe and {P}ecquerie, {L}aure},
  editor = {},
  language = {{ENG}},
  abstract = {{U}nprecedented quantities of the brown floating macroalgae {S}argassum have been recorded in the tropical {N}orth {A}tlantic {O}cean. {H}owever, the environmental factors affecting holopelagic {S}argassum spp. growth and survival remain poorly understood. {H}ere, we developed a multi-reserve {DEB} model for {S}argassum spp. to link environmental conditions (temperature, nutrients, and light) to the organism physiology. {I}n the context of {DEB} theory, estimating a multi-reserve model parameters can be particularly challenging and strongly relies on the availability of the datasets with information about physiological processes. {W}e conducted a literature review of {S}argassum spp. physiological responses, and although some data have been reported, experimental datasets on some key physiological processes are still relatively scarce. {F}rom the available data we performed an estimation of the {DEB} model parameters. {W}e then followed a "virtual ecologist" approach to create a framework linking modelers and empiricists, to analyze which experiments that are most needed to reduce parameter uncertainty. {W}e tested parameter identifiability by creating "virtual" observed data and we analyzed the type of datasets that reduce the uncertainty on parameter estimates, thus increasing their identifiability and the prediction power of the algae model. {O}ur analysis showed to which extent new experiments on nutrient uptake and nutrient limitation would reduce the uncertainty of key model parameters and improve our understanding of holopelagic {S}argassum spp. physiology. {M}ore generally, our study demonstrates how the use of {DEB} models, coupled with parameter identifiability analyses, can help design most needed experiments thereby contributing to an integrated approach between experiments and modeling.},
  keywords = {{P}arameter estimation ; {B}ioenergetics ; {M}acroalgae ; {V}irtual ecologist approach ; {E}xperimental design ; {ATLANTIQUE} ; {ATLANTIQUE} {NORD} ; {ZONE} {TROPICALE}},
  booktitle = {},
  journal = {{E}cological {M}odelling},
  volume = {516},
  numero = {},
  pages = {111578 [15 p.]},
  ISSN = {0304-3800},
  year = {2026},
  DOI = {10.1016/j.ecolmodel.2026.111578},
  URL = {https://www.documentation.ird.fr/hor/fdi:010096926},
}