The influence of multiple controls on structural and functional characteristics of macroinvertebrate community in a regulated Alpine river

Abstract

In the past 30 years, several studies have proved that the river flow regime is fundamental in structuring biotic communities. The condition of the ecosystem results not only from the occurrence of extreme events, such as floods and droughts but also from habitat availability and from its temporal variation. Describing the relationships between macroinvertebrate community characteristics and environmental gradients of flow, temperature, nutrient supplies, and habitat conditions is fundamental to understand ecological dynamics. This is the basis for predicting changes within the communities and in ecosystem functions and ultimately to properly manage and conserve the riverine ecosystems. Seven sites, along a 20‐km river sector, were surveyed for macroinvertebrates and water chemistry seasonally, from 2012 to 2016. Habitat conditions were assessed along a 500‐m stretch in each site. The river discharge was continuously monitored by two water level recorders and used to reconstruct various hydrological indices specific for each sampling location. During the sampling period, numerous high flow events and some prolonged periods of low flow were observed. Quantile regression was used to describe the effects of potential limiting factors on macroinvertebrate community, which were primarily driven by antecedent flow conditions and season whereas habitat conditions and water chemistry played only a minor role. Quantitative models have been developed to predict structural and functional characteristics of macroinvertebrate community as a function of antecedent flow conditions, habitat, and physicochemical water characteristics. Those models allow to identify the main drivers and predict the effect of different water management strategies to riverine ecosystem.

Local contributions to beta diversity in urban pond networks: Implications for biodiversity conservation and management

“…Each statistical set modelled the influence of taxonomic richness via 4 statistical functions-linear, quadratic, exponential and logarithmic (sensu Fornaroli et al, 2019). For statistical sets performed on individual settlement datasets, traditional regression models (y = αx + β + ε) were employed.…”

Effects of high-altitude reservoirs on the structure and function of lotic ecosystems: a case study in Italy

“…Some authors reported that in high alpine streams, the anthropogenic flow regulation tended to ameliorate stream conditions resulting in higher diversity but this did not favor certain species that are specialist in the harsh natural conditions (Füreder et al, 2000). Although further work is required to address the impact of taxonomic resolution, our results highlights how important is the definition of the reference condition (i.e., expected community composition in pristine sites such as S1 and S2) for bioassessment (Wilding et al, 2018;Fornaroli et al, 2019) and how biomonitoring indices must account for the deviation from the reference condition both as increases or decreases in diversity and abundance of organisms.…”

Flow regimes control the establishment of invasive crayfish and alter their effects on lotic macroinvertebrate communities

“…The alternative QR and QMR models tested each hydrological index (and its interaction with treatment) via four statistical functions (Linear, Exponential, Logarithmic and Quadratic; sensu Fornaroli, Calabrese, Marazzi, Zaupa, & Mezzanotte, ). Testing for this interaction provided a means of examining whether P. leniusculus modified macroinvertebrate community responses to hydrological variability.…”

“…Finally, to determine the significance of each qualifying QR and QMR, the average w i was compared against that of a single null model exhibiting the same model structure, but without a hydrological index, treatment or their interactive effect (in a process analogous to a likelihood ratio test). For this, an alternative model exhibiting an average w i greater than 0.75 was considered significant (Fornaroli et al, ).…”