Quantitative reconstruction of past salinity variations in African lakes: assessment of chironomid-based inference models (Insecta: Diptera) in space and time

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Abstract:

Faunal records of 20 common midge species (Diptera: Chironomidae) in 32 African surface waters with salinities ranging from 20 to 41 000 µS·cm–1 were used to develop inference models for quantitative reconstruction of past salinity variations from larval chironomid fossils preserved in lake sediments. Weighted-averaging regression and calibration models using presence–absence data (P/A) and presence–absence data with tolerance down-weighting (P/Atol) produced bootstrapped coefficients of determination (r2) of 0.78 and 0.81, respectively, and root mean squared errors (RMSE) of prediction of 0.42 and 0.39 log conductivity units. Historical conductivity data from African lakes are scarce. Therefore, model performance was tested in time by comparing chironomid-inferred conductivity estimates with the corresponding diatom-inferred estimates in sediment records of two fluctuating lakes in the Rift Valley of Kenya. A hybrid procedure in which presence–absence calibration models were applied to abundance-weighted fossil data yielded significantly higher correlation between chironomid- and diatom-inferred time series (Lake Oloidien AD 1880–1991, r2 = 0.76–0.78; Crescent Island Crater AD 900–1993, r2 = 0.56–0.61) than by applying the same models to presence–absence fossil data (r2 = 0.47–0.56 and 0.26–0.42, respectively). Overall, model performance confirms that Chironomidae are valuable bioindicators for natural and man-made changes in the water balance of African lakes.

Nous avons combiné les données de la répartition de 20 espèces de moucherons (Diptères: Chironomidae) dans 32 lacs africains aux salinités mésurant entre 20 µS·cm–1 et 41 000 µS·cm–1 avec des données chimiques de ces lacs et développé des modèles de déduction pour la reconstruction de variations de salinité à partir d'assemblages de chironomides fossiles préservés dans les sédiments lacustres. Les modèles de régression et d'étalonnage à pondération de moyenne utilisant des donneés présence–absence (P/A) ou présence–absence avec minorisation des tolérances (P/Atol) produisaient des coefficients de détermination (r2) de 0,78 et 0,81 et des erreurs quadratique moyenne bootstrap (RMSE) de 0,42 et 0,39. De mesures historiques de salinité provenant des lacs Africains étant assez rare, les testes de performance de ces modèles dans le domaine temporel ont été fait aussi par comparer les estimations de salinité passées déduites des chironomides avec celles déduites des diatomées dans les enregistrements paléolimnologiques de deux lacs fluctuants dans la Vallée du Rift au Kenya. Un procédé hybride applicant les modèles d'étalonnage présence–absence aux données fossiles d'abondances ponderées a réalisé des corrélations (Lake Oloidien AD 1880–1991, r2 = 0,76–0,78; Crescent Island Crater AD 900–1993, r2 = 0,56–0,61) supérieures aux celles obtenus par applicant les mêmes modèles aux données fossiles présence–absence. La performance de ces modèles confirme le potentiel des Chironomides fossiles en tant qu'indicateurs aux changements climatiques et anthropogènes de la hydrologie des lacs africains.

Document Type: Research Article

Publication date: June 1, 2004

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  • Published continuously since 1901 (under various titles), this monthly journal is the primary publishing vehicle for the multidisciplinary field of aquatic sciences. It publishes perspectives (syntheses, critiques, and re-evaluations), discussions (comments and replies), articles, and rapid communications, relating to current research on cells, organisms, populations, ecosystems, or processes that affect aquatic systems. The journal seeks to amplify, modify, question, or redirect accumulated knowledge in the field of fisheries and aquatic science. Occasional supplements are dedicated to single topics or to proceedings of international symposia.
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