An understanding of the extent to which natural variability has been and is being exceeded by the effects of human activity can make an important contribution to the effective management of impacted water bodies, including their restoration. Frequently, however, the required monitoring data are not available, particularly for the period prior to human impact, or are of insufficient quality. Two methodological solutions to this problem are often proposed, both of which involve the reconstruction of past variations in water quality and associated ecological conditions through indirect means: computer (hindcast) modelling and sedimentary (palaeolimnological) analyses. Both proposed solutions are not without their own challenges, however. Here a series of dynamic computer models (a catchment model and an in-lake ecological response model) and palaeolimnological techniques (including sediment-based diatom-inferred total phosphorus, DI-TP), were used to reconstruct total phosphorus (TP) concentrations and measures of primary productivity in Lough Mask, Co. Mayo, for the period AD 1905 2006. Although results from both approaches indicated similar patterns of nutrient enrichment in the lake during the twentieth century, sediment-based DI-TP values were consistently higher than hindcast-modelled in-lake TP concentrations. Both approaches indicated oligotrophic to mesotrophic conditions in Lough Mask prior to c. AD 1950. Elevated trophic conditions (in the range mesotrophic eutrophic) were evident from c. AD 1970. Modelling results indicated that increased diffuse phosphorus loading from agricultural sources was the main driver of nutrient enrichment from c. AD 1970. Eutrophication was also concurrent with climatic warming, which was manifested in strengthened thermal stratification in model simulations. Results generated by the two approaches suggest that pre-AD 1950 trophic conditions could be used as a reference baseline, representing conditions prior to major impacts from agricultural intensification, for defining current water quality management targets.
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