Operator and replicability bias in comparative taphonomic studies

The operator effect is a well-known methodological bias already quantified in some taphonomic studies. However, the replicability effect, i.e., the use of taphonomic attributes as a replicable scientific method, has not been taken into account to the present. Here, we quantified for the first time this replicability bias using different multivariate statistical techniques, testing if the operator effect is related to the replicability effect. We analyzed the results reported by 15 operators working on the same dataset. Each operator analyzed 30 biological remains (bivalve shells) from five different sites, considering the attributes fragmentation, edge rounding, corrasion, bioerosion and secondary color. The operator effect followed the same pattern reported in previous studies, characterized by a worse correspondence for those attributes having more than two levels of damage categories. However, the effect did not appear to have relation with the replicability effect, because nearly all operators found differences among sites. Despite the binary attribute bioerosion exhibited 83% of correspondence among operators it was the taphonomic attributes that showed the highest dispersion among operators (28%). Therefore, we conclude that binary attributes (despite showing a reduction of the operator effect) diminish replicability, resulting in different interpretations of concordant data. We found that a variance value of nearly 8% among operators, was enough to generate a different taphonomic interpretation, in a Q-mode cluster analysis. The results reported here showed that the statistical method employed influences the level of replicability and comparability of a study and that the availability of results may be a valid alternative to reduce bias.

Daily mean surface meteorology and river discharge in Central Sulawesi for the period 2002-2005

The El Niño/ Southern Oscillation (ENSO) phenomenon is the strongest known natural interannual climate fluctuation. The most recent two extreme ENSO events of 1982/83 and 1997/98 severley hit the socio-economy of main parts of Indonesia. As the climate variability is not homogeneous over the whole Archipelago of Indonesia, ENSO events cause negative precipitation anomalies of diverse magnitude and uration in different regions. Understanding the hydrology of humid tropical catchments is an essential prerequisite to investigate the impact of climate variability on the catchment hydrology. Together with the quantitative assessment of future water resource changes they are essential tools to develop mitigation strategies on a catchment scale. These results can be integrated into long term Integrated Water Resource Management (IWRM) strategies. The general objective of this study is to investigate and quantify the impact of ENSO caused climate variability on the water balance and the implications for water resources of a mesoscale tropical catchment.