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Lampetra zanandreai (Vladykov, 1955) is a non-parasitic, freshwater lamprey endemic to the ancient Po basin. A few, mostly very dated studies have investigated some aspect of the biology of this lamprey, but surprisingly, despite it being considered a threatened species, information on its ecology is practically absent. Specifically, information about habitat preferences is generic and qualitative. Since most of the life cycle is spent in the fossorial larval stage, which is also the only one in which organisms feed, information about ecological requirements of ammocoetes is essential for any conservation strategy. In this study we provide the first data about physical habitat preferences for lamprey ammocoetes by analyzing their presence within sampled hydromorphological units (HMUs), following the approach of habitat attribute description of the MesoHABSIM (MesoHABitat SImulation Model) methodology. To explore the relationship between lamprey presence and HMU characteristics, a random forest (RF) model was developed and tested using data collected in five stream reaches of the Po basin (NW Italy). The final parsimonious RF model performed well in terms of accuracy (95.2%) and true skill statistic (90.4%), allowing us to identify the most significant mesohabitat attributes for the considered species. Furthermore, in the Ghiandone River, where the highest density and number of individuals were found, a granulometric analysis of the riverbed material was carried out. Results showed that selected strains of sand and fine gravel, with low organic content, are preferred by ammocoetes. To our knowledge, this is the first study exploring the habitat preference of this endangered species, listed in Annex II of the European Habitats Directive. [ABSTRACT FROM AUTHOR]

Habitat models rarely consider macroinvertebrate communities as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the whole community. This research aimed at providing an approach to model the habitat of the macroinvertebrate communities. The study was carried out in three rivers, located in Italy and characterized by a braiding morphology, gravel riverbeds, and low flows during the summer period. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the mesohabitat scale. Using different datasets gathered from field data collection and 2D hydrodynamic simulations, the model was calibrated in the Trebbia River (2019 field campaign) and validated in the Trebbia, Taro, and Enza rivers (2020 field campaign). The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R 2 coefficient (R 2 cv ) of the training dataset was 0.71, whereas the R 2 coefficient (R 2 test ) for the validation dataset was 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and river morphological modifications. Lastly, the proposed approach allowed to extend the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to ecological flows design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)