Biometric conversion factors as a unifying platform for comparative assessment of invasive freshwater bivalves

Invasive bivalves continue to spread and negatively impact freshwater ecosystems worldwide. As different metrics for body size and biomass are frequently used within the literature to standardise bivalve‐related ecological impacts (e.g. respiration and filtration rates), the lack of broadly applicable conversion equations currently hinders reliable comparison across bivalve populations. To facilitate improved comparative assessment among studies originating from disparate geographical locations, we report body size and biomass conversion equations for six invasive freshwater bivalves (or species complex members) worldwide: Corbicula fluminea, C. largillierti, Dreissena bugensis, D. polymorpha, Limnoperna fortunei and Sinanodonta woodiana, and tested the reliability (i.e. precision and accuracy) of these equations. Body size (length, width and height) and biomass metrics of living‐weight (LW), wet‐weight (WW), dry‐weight (DW), dry shell‐weight (SW), shell free dry‐weight (SFDW) and ash‐free dry‐weight (AFDW) were collected from a total of 44 bivalve populations located in Asia, the Americas and Europe. Relationships between body size and individual biomass metrics, as well as proportional weight‐to‐weight conversion factors, were determined. For most species, although inherent variation existed between sampled populations, body size directional measurements were found to be good predictors of all biomass metrics (e.g. length to LW, WW, SW or DW: R2 = 0.82–0.96), with moderate to high accuracy for mean absolute error (MAE): ±9.14%–24.19%. Similarly, narrow 95% confidence limits and low MAE were observed for most proportional biomass relationships, indicating high reliability for the calculated conversion factors (e.g. LW to AFDW; CI range: 0.7–2.0, MAE: ±0.7%–2.0%). Synthesis and applications. Our derived biomass prediction equations can be used to rapidly estimate the biologically active biomass of the assessed species, based on simpler biomass or body size measurements for a wide range of situations globally. This allows for the calculation of approximate average indicators that, when combined with density data, can be used to estimate biomass per geographical unit‐area and contribute to quantification of population‐level effects. These general equations will support meta‐analyses, and allow for comparative assessment of historic and contemporary data. Overall, these equations will enable conservation managers to better understand and predict ecological im