Biology subjects

Pinardi, M.

Publications and source records attributed to Pinardi, M..

3 recordsLinked to original sources

bioRxiv2020

Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species

Macrophytes are key players in aquatic ecosystems diversity, but knowledge on variability of their functional traits, among and within species, is still limited. Remote sensing is a high-throughput, feasible option for characterizing plant traits at different scales, provided that reliable spectroscopy models are calibrated with congruous empirical data. We sampled leaves from six floating and emergent macrophyte species common in temperate areas, covering different phenological stages, seasons, and environmental conditions, and measured leaf reflectance (400-2500 nm) and leaf traits (dealing with photophysiology, pigments and structure). We explored optimal spectral bands combinations and established non-parametric reflectance-based models for selected traits, eventually showing how airborne hyperspectral data can capture spatial-temporal macrophyte variability. Our key finding is that structural - leaf dry matter content, leaf mass per area - and biochemical - chlorophyll-a content and chlorophylls to carotenoids ratio - traits can be surrogated by leaf reflectance with relative error under 20% across macrophyte species, while performance of reflectance-based models for photophysiological traits depends on species. This finding shows the link between leaf reflectance and leaf economics (structure and biochemistry) for aquatic plants, thus supporting the use of remote sensing for enhancing the level of detail of macrophyte functional diversity analysis, to intra-site and intra-species scales.

ecology↗

bioRxiv2018

Aspects of invasiveness of Ludwigia and Nelumbo in shallow temperate fluvial lakes

The relationship between invasive plant functional traits and their invasiveness is still the subject of scientific investigation, and the backgrounds of transition from non-native to invasive species in ecosystems are therefore poorly understood. Furthermore, our current knowledge on species invasiveness is heavily biased toward terrestrial species; we know much less about the influence of allochthonous plant traits on their invasiveness in aquatic ecosystems. We studied physiological and ecological traits of two introduced and three native macrophyte species in the Mantua lakes system (northern Italy). We compared their photophysiology, pigment content, leaf reflectance, and phenology in order to assess how the invasive Nelumbo nucifera and Ludwigia hexapetala perform compared to native species, Nuphar lutea, Nymphaea alba, and Trapa natans. We found L. hexapetala to have higher photosynthetic efficiency and able to tolerate higher light intensities than N. nucifera and the native species especially at extreme weather conditions (prolonged exposure to high light and higher temperatures). Chlorophyll a and b, and carotenoid contents of both allochthonous species was substantially higher than that of the native plants suggesting adaptive response to the ecosystem of Mantua lakes system. Higher variability of recorded data in invasive species also was observed. These observations suggest advanced photosynthetic efficiency of the invasive species, especially L. hexapetala, resulting in faster growth rates and higher productivity. This was supported by the evaluation of seasonal dynamics mapped from satellite remote sensing data. This study provides empirical evidence for the relationship between specific plant physiological traits and invasiveness of aquatic plant species, highlighting the importance of trait studies in predicting ecosystem-level impacts of invasive plant species.

ecology↗

bioRxiv2018

Assessing macrophyte seasonal dynamics using dense time series of medium resolution satellite data

Thanks to the improved spatial and temporal resolution of new generation Earth Observation missions, such as Landsat 8 and Sentinel-2, the potential of remote sensing techniques in mapping land surface phenology of terrestrial biomes can now be tested in inland water systems.\n\nWe assessed the capabilities of dense time series of medium resolution satellite data to deliver quantitative information about macrophyte phenology metrics, focusing on three temperate European shallow lakes with connected wetlands, located in Italy, France and Romania.\n\nLeaf area index (LAI) maps for floating and emergent macrophyte growth forms were derived from semi-empirical regression modelling based on the best performing spectral index, with an error level around 0.11 m2 m-2. Phenology metrics were computed from LAI time series using TIMESAT code and used to analyse macrophyte seasonal dynamics in terms of spatial patterns and species-dependent variability. Peculiar patterns of autochthonous and allochthonous species seasonality across the three study areas were related to the environmental characteristics of each area in terms of ecological and hydrological conditions.\n\nIn addition, the influence of satellite dataset characteristics - i.e. cloud cover thresholding, temporal resolution and missing acquisitions - on phenology timing metrics retrieval was assessed. Results have shown that with full resolution (5-day revisit) time series, cloud cover can bias phenology timing metrics by less than 2 days, and that reducing temporal resolution to 15 days (similar to Landsat revisit) still allows for mapping the start and peak of macrophyte growth with an error level around 2-3 days.

ecology↗