Effects of Paramuricea clavata (Risso, 1826) (Anthozoa: Plexauridae) forests on settlement of benthic species: an experimental approach

Rationale: Coralligenous habitat is considered the second most important subtidal “hot spot” of species diversity in the Mediterranean Sea after the Posidonia oceanica meadows. It can be defined as a typical Mediterranean biogenic hard bottom, mainly produced by the accumulation of calcareous encrusting algae that, together with other builder organisms, form a multidimensional framework with a high micro-spatial variability. The development of this habitat depends on physical factors (i.e. light, hydrodynamism, nutrients, etc.), but also biologic interactions can play a relevant role in structuring the benthic assemblages. This great environmental heterogeneity allows several different assemblages to coexist in a reduced space. One of the most beautiful is that characterised by the Mediterranean gorgonian Paramuricea clavata (Risso, 1826) that can contribute to above 40% of total biomass of the community and brings significant structural complexity into the coralligenous habitat. In sites moderately exposed to waves and currents, P. clavata can form high-density populations (up to 60 colonies m-2) between 20 – 70 m in depth. Being a suspension feeder, where it forms dense populations, P. clavata plays a significant role in transferring energy from planktonic to benthic system. The effects of the branched colonies of P. clavata could be comparable to those of the forests on land. They can affect the micro scale hydrodynamism and light, promoting or inhibiting the growth of other species. Unfortunately, gorgonians are threatened by several anthropogenic disturbance factors (i.e. fishing, pollution, tourism) and by climatic anomalies, linked to the global changes, that are responsible of thermal stress, development of mucilage and enhanced pathogens activity, leading to mass mortality events in last decades. Till now, the possible effects of gorgonian forest loss are largely unknown. Our goal was to analyse the ecological role of these sea fan forests on the coralligenous benthic assemblages. Experimental setup and main results: The influence of P. clavata in the settlement and recruitment of epibenthic organisms was analysed by a field experiment carried out in two randomly selected places: Tavolara island and Portofino promontory. The experiment consisted in recreate the presence and absence of the gorgonian forest on recruitment panels, arranged in four plots per type (forested and non-forested), interspersed each other, and deployed at the same depth. On every forested panel 3 gorgonian colonies about 20 cm height were grafted with the use of Eppendorf tubes and epoxy resin bicomponent simulating a density of 190 sea fans per m-2. This density corresponds to a mean biomass of 825 g DW m-2,3 which is of the same order of magnitude of the natural high-density populations. After about 4 months, the panels were collected and analysed in laboratory in order to estimate the percent cover of all the species that have colonized the substrata. The gorgonian forest effects were tested by multivariate and univariate permutational analyses of the variance (PERMANOVA). Recruited assemblages largely differed between the two study sites, probably due to different environmental conditions including water quality and turbidity. On overall, the presence of P. clavata reduced the settlement and recruitment of several algae: the shadow caused by the gorgonian might reduce light availability and therefore their growth. This effect might be greater in places where the waters are on average more clear, since at Portofino it is less visible and could be masked by the high turbidity of the water. The same pattern was registered for forams, more abundant outside gorgonian forest, probably linked with algal distribution, shadowing effect or alimentary competition. The last one hypothesis could be valid also for serpulids polychaetes that growth mainly on non-forested panels. An opposite trend, was showed by a species of bryozoan and by an hydroid that is facilitated by the presence of P. clavata, probably because it attenuates irradiance level and hydrodynamism. Species diversity was significantly reduced by the presence of P. clavata forests at both sites. This seems in contrast with what we expected, but the result may be influenced by the large algal component on non-forested panels. The analysis confirmed the presence of differences in the species diversity among plots and between sites respectively due to natural high variability of the coralligenous system and to different local environment conditions. The reduction of species diversity due to the presence of gorgonians appeared related to a worst evenness rather than to less species richness. With our experiment it is demonstrated that the presence of P. clavata forests can significantly alter local coralligenous assemblages patterns, promoting or inhibiting the recruitment of some species, modifying trophic relationships and adding heterogeneity and complexity to the habitat. Moreover, P. clavata could have a stabilising effect on the coralligenous assemblages.

Assessing the relationship between bee/flower diversity and vegetation structural heterogeneity through UAV photogrammetry

The ecosystem services provided by bees are very important. Factors as habitat fragmentation, intensive agriculture and climate change are contributing to the decline of bee populations. The use of remote sensing could be a useful tool for the recognition of sites with a high diversity, before performing a more expensive survey in the field. In this study the ability of Unmanned Aerial Vehicles (UAV) images to estimate biodiversity at local scale has been analysed testing the concept of the Height Variation Hypothesis (HVH). This approach states that, the higher the vegetation height heterogeneity (HH) measured by remote sensing information, the higher the vertical complexity and the higher vegetation species diversity. In this thesis the concept has been brought to a higher level, in order to understand if the vegetation HH can be considered a proxy also of bee species diversity and abundance. We tested this approach collecting field data on bees/flowers and RGB images through an UAV campaign in 30 grasslands in the South of the Netherlands. The Canopy Height Model (CHM) were derived through the photogrammetry technique "Structure from Motion" (SfM) with resolutions of 10cm, 25cm, 50cm. Successively, the HH assessed on the CHM using the Rao's Q heterogeneity index was correlated to the field data (bee abundance, diversity and bee/flower species richness). The correlations were all positive and significant. The highest R2 values were found when the HH was calculated at 10cm and correlated to bee species richness (R2 = 0.41) and Shannon’s H index (R2 = 0.38). Using a lower spatial resolution the goodness of fit slightly decreases. For flower species richness the R2 ranged between 0.36 to 0.39. Our results suggest that methods based on the concept behind the HVH, in this case deriving information of HH from UAV data, can be developed into valuable tools for large-scale, standardized and cost-effective monitoring of flower diversity and of the habitat quality for bees.

Flower cover and bee diversity estimate by drone RGB images

Worldwide, biodiversity is decreasing due to climate change, habitat fragmentation and agricultural intensification. Bees are essential crops pollinator, but their abundance and diversity are decreasing as well. For their conservation, it is necessary to assess the status of bee population. Field data collection methods are expensive and time consuming thus, recently, new methods based on remote sensing are used. In this study we tested the possibility of using flower cover diversity estimated by UAV images (FCD-UAV) to assess bee diversity and abundance in 10 agricultural meadows in the Netherlands. In order to do so, field data of flower and bee diversity and abundance were collected during a campaign in May 2021. Furthermore, RGB images of the areas have been collected using Unmanned Aerial Vehicle (UAV) and post-processed into orthomosaics. Lastly, Random Forest machine learning algorithm was applied to estimate FCD of the species detected in each field. Resulting FCD was expressed with Shannon and Simpson diversity indices, which were successively correlated to bee Shannon and Simpson diversity indices, abundance and species richness. The results showed a positive relationship between FCD-UAV and in-situ collected data about bee diversity, evaluated with Shannon index, abundance and species richness. The strongest relationship was found between FCD (Shannon Index) and bee abundance with R2=0.52. Following, good correlations were found with bee species richness (R2=0.39) and bee diversity (R2=0.37). R2 values of the relationship between FCD (Simpson Index) and bee abundance, species richness and diversity were slightly inferior (0.45, 0.37 and 0.35, respectively). Our results suggest that the proposed method based on the coupling of UAV imagery and machine learning for the assessment of flower species diversity could be developed into valuable tools for large-scale, standardized and cost-effective monitoring of flower cover and of the habitat quality for bees.