Lorenzo Tancioni

Weak Concordance between Fish and Macroinvertebrates in Mediterranean Streams

Although anthropogenic degradation of riverine systems stimulated a multi-taxon bioassessment of their ecological integrity in EU countries, specific responses of different taxonomic groups to human pressure are poorly investigated in Mediterranean rivers. Here, we assess if richness and composition of macroinvertebrate and fish assemblages show concordant variation along a gradient of anthropogenic pressure in 31 reaches across 13 wadeable streams in central Italy. Fish and invertebrate taxonomic richness was not correlated across sites. However, Mantel test showed that the two groups were significantly, albeit weakly, correlated even after statistically controlling for the effect of environmental variables and site proximity. Variance partitioning with partial Canonical Correspondence Analysis showed that the assemblages of the two groups were influenced by different set of environmental drivers: invertebrates were influenced by water organic content, channel and substratum features, while fish were related to stream temperature (mirroring elevation) and local land-use. Variance partitioning revealed the importance of biotic interactions between the two groups as a possible mechanisms determining concordance. Although significant, the congruence between the groups was weak, indicating that they should not be used as surrogate of each other for environmental assessments in these Mediterranean catchments. Indeed, both richness and patterns in nestedness (i.e. where depauperate locations host only a subset of taxa found in richer locations) appeared influenced by different environmental drivers suggesting that the observed concordance did not result from a co-loss of taxa along similar environmental gradients. As fish and macroinvertebrates appeared sensitive to different environmental factors, we argue that monitoring programmes should consider a multi-assemblage assessment, as also required by the Water Framework Directive.

Scale dependent biodiversity patterns in Mediterranean river catchments: a multi taxa approach

Although the important contribution of β-diversity to regional (γ) diversity is increasingly recognised, our understanding of how the spatial scaling of β-diversity differs among taxonomic groups is still limited, especially in dynamic lotic ecosystems. In this study, we assessed the difference in the partitioning of diversity at nested spatial scales, from reach to catchment, among riparian birds, fish and benthic macroinvertebrates in Mediterranean river systems. Fish and macroinvertebrates showed similar scaling patterns, with β-diversity always larger than expected by a random distribution of individuals at all spatial scales (among reaches, rivers and catchments), and local (α) diversity always lower than expected. Conversely, β-diversity of riparian birds appeared larger than expected only at the largest scale (among catchments), while local diversity did not differ from random expectation. For birds, however, results partly depended on the weighting of abundant and rare species. Although the relative contribution of β to γ-diversity did not differ substantially among groups (with multiplicative β representing five to six distinct communities), its deviation from random expectations showed marked differences indicating that functionally different groups exhibit distinct spatial patterns. This study is among the first to investigate scaling patterns in β-diversity across taxonomic groups with different ecological requirements and dispersal ability, and provides a holistic picture of riverine biodiversity. From a conservation perspective, the results suggest that, in these river systems, flexible conservation strategies are required in order to protect multiple taxonomic groups.

Gonadal disorder in the thinlip grey mullet (Liza ramada, Risso 1827) as a biomarker of environmental stress in surface waters.

The aim of this study was to evaluate the use of gonadal alterations in the thinlip grey mullet (Liza ramada) as a biological indicator in assessing aquatic ecosystems health, with particular emphasis to river ecosystems exposed to sewage discharges. For this purpose, the reproductive status and the presence of gonadal alterations were studied in 206 mullets collected from two sites on the low course of the Tiber River, downstream of a large urban sewage treatment plant and in the estuarine area, and from an uncontaminated pond considered as reference site. Intersex and irregularly shaped gonads were observed in 20.8% of the mullets from the most polluted site, and intersex gonads in 10.3% of those from the estuarine area. No alterations were detected in the fish from the reference site, which also showed distinct stages of gonadal development. Conversely, unclear stages of testicular and ovary development were observed in the fish from the two polluted river sites. The results of this study suggest that L. ramada may represent a sentinel species in environmental risk assessment and support the use of gonadal alterations of this species as a bioindicator for extensive monitoring of pollution in lower stretches of rivers and estuarine areas.

Cascaded neural networks improving fish species prediction accuracy: the role of the biotic information

Species distribution is the result of complex interactions that involve environmental parameters as well as biotic factors. However, methodological approaches that consider the use of biotic variables during the prediction process are still largely lacking. Here, a cascaded Artificial Neural Networks (ANN) approach is proposed in order to increase the accuracy of fish species occurrence estimates and a case study for Leucos aula in NE Italy is presented as a demonstration case. Potentially useful biotic information (i.e. occurrence of other species) was selected by means of tetrachoric correlation analysis and on the basis of the improvements it allowed to obtain relative to models based on environmental variables only. The prediction accuracy of the L. aula model based on environmental variables only was improved by the addition of occurrence data for A. arborella and S. erythrophthalmus. While biotic information was needed to train the ANNs, the final cascaded ANN model was able to predict L. aula better than a conventional ANN using environmental variables only as inputs. Results highlighted that biotic information provided by occurrence estimates for non-target species whose distribution can be more easily and accurately modeled may play a very useful role, providing additional predictive variables to target species distribution models.