Integrating low-altitude drone based-imagery and OBIA for mapping and manage semi natural grassland habitats.

Monitoring semi-natural grasslands is difficult and costly because they occur in highly dynamic and extremely complex habitat mosaics. We combined the use of a low-cost unmanned aerial vehicle (UAV) and Structure from Motion (SfM) photogrammetry to acquire high spatial resolution (∼1.5 cm pixel) RGB imagery. After image classification through Object-Based Image Analysis (OBIA), we accurately were able to distinguish three semi-natural grassland types, one of which is a habitat of conservation concern. The use of orthomosaics, digital elevation models (DEMs), and canopy height models (CHMs) yielded excellent overall classification accuracies (>89%) assessed through both remotely validated and ground-truthed points. We identified two layers of woody vegetation with a user's (UA) and producer's (PA) accuracies >73% and three grassland types: closed grassland (UA = 94%; PA = 97%), open grassland habitat (UA = 97%; PA = 93%) and open grasslands with soil erosion (UA = 96%; PA = 98%). The grassland types differed substantially in the cover of vegetation, rocks, stones, and bare soil measured in the field, as well as in the number and relative cover of the habitat diagnostic species. The proposed methodology is highly promising for mapping and monitoring semi-natural grassland of conservation concern in support of tailored management actions.

Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity.

Many coastal ecosystems, such as coral reefs and seagrass meadows, currently experience overgrowth by fleshy algae due to the interplay of local and global stressors. This is usually accompanied by strong decreases in habitat complexity and biodiversity. Recently, persistent, mat-forming fleshy red algae, previously described for the Black Sea and several Atlantic locations, have also been observed in the Mediterranean. These several centimetre high mats may displace seagrass meadows and invertebrate communities, potentially causing a substantial loss of associated biodiversity. We show that the sessile invertebrate biodiversity in these red algae mats is high and exceeds that of neighbouring seagrass meadows. Comparative biodiversity indices were similar to or higher than those recently described for calcifying green algae habitats and biodiversity hotspots like coral reefs or mangrove forests. Our findings suggest that fleshy red algae mats can act as alternative habitats and temporary sessile invertebrate biodiversity reservoirs in times of environmental change.

High spatial resolution underwater data for mapping seagrass transplantation: A powerful tool for visualization and analysis.

These datasets derived from our mapping protocol are presented as a research article in the Journal of Environmental Management [1]. In particular, by using a Structure from Motion photogrammetric workflow we produced high spatial resolution 2D raster maps and 3D outputs such as dense points clouds and textured meshes of an underwater seagrass restoration site. In this area transplanted fragments of Posidonia oceanica were planted to restore this impacted site after the Costa Concordia shipwrecking which occurred on 13 January 2012 along the NE coast of Giglio Island (Tuscany, Italy). Photogrammetric outputs were used to render the underwater environment by using the open-source software Blender allowing a fine 3D modelling and immersive visualization of the mapped area. This data other than providing an exceptional tool for analysing the benthic habitats from a biological point of view, following over time the progress transplanting operations, might also provide a new way to visualize and share the perception of such underwater shallow environments to a large plethora of users, increasing the public awareness on restoration programmes and promoting new action aimed at restored underwater habitats restoration.

Seagrass restoration monitoring and shallow-water benthic habitat mapping through a photogrammetry-based protocol.

Seagrasses rank among the most productive yet highly threatened ecosystems on Earth. Loss of seagrass habitat because of anthropogenic disturbances and evidence of their limited resilience have provided the impetus for investigating and monitoring habitat restoration through transplantation programmes. Although Structure from Motion (SfM) photogrammetry is becoming a more and more relevant technique for mapping underwater environments, no standardised methods currently exist to provide 3-dimensional high spatial resolution and accuracy cartographic products for monitoring seagrass transplantation areas. By synthesizing various remote sensing applications, we provide an underwater SfM-based protocol for monitoring large seagrass restoration areas. The data obtained from consumer-grade red-green-blue (RGB) imagery allowed the fine characterization of the seabed by using 3D dense point clouds and raster layers, including orthophoto mosaics and Digital Surface Models (DSM). The integration of high spatial resolution underwater imagery with object-based image classification (OBIA) technique provided a new tool to count transplanted Posidonia oceanica fragments and estimate the bottom coverage expressed as a percentage of seabed covered by such fragments. Finally, the resulting digital maps were integrated into Geographic Information Systems (GIS) to run topographic change detection analysis and evaluate the mean height of transplanted fragments and detect fine-scale changes in seabed vector ruggedness measure (VRM). Our study provides a guide for creating large-scale, replicable and ready-to-use products for a broad range of applications aimed at standardizing monitoring protocols in future seagrass restoration actions.

Capitoline Dolphins: Residency Patterns and Abundance Estimate of Tursiops truncatus at the Tiber River Estuary (Mediterranean Sea).

Periodic assessments of population status and trends to detect natural influences and human effects on coastal dolphin are often limited by lack of baseline information. Here, we investigated for the first time the site-fidelity patterns and estimated the population size of bottlenose dolphins (Tursiops truncatus) at the Tiber River estuary (central Mediterranean, Tyrrhenian Sea, Rome, Italy) between 2017 and 2020. We used photo-identification data and site-fidelity metrics to study the tendency of dolphins to remain in, or return to, the study area, and capture-recapture models to estimate the population abundance. In all, 347 unique individuals were identified. The hierarchical cluster analysis highlighted 3 clusters, labeled resident (individuals encountered at least five times, in three different months, over three distinct years; n = 42), part-time (individuals encountered at least on two occasions in a month, in at least two different years; n = 73), and transient (individuals encountered on more than one occasion, in more than 1 month, none of them in more than 1 year; n = 232), each characterized by site-fidelity metrics. Open POPAN modeling estimated a population size of 529 individuals (95% CI: 456-614), showing that the Capitoline (Roman) coastal area and nearby regions surrounding the Tiber River estuary represent an important, suitable habitat for bottlenose dolphins, despite their proximity to one of the major urban centers in the world (the city of Rome). Given the high number of individuals in the area and the presence of resident individuals with strong site fidelity, we suggest that conservation plans should not be focused only close to the Tiber River mouths but extended to cover a broader scale of area.