Effects of different hypoxia timing regimes on a transitional habitat's ( Pialassa Baiona, Ravenna, Italy) benthic community.

The aim of this thesis was to quantify experimentally in the field the effects of different timing regimes of hypoxia on the structure of benthic communities in a transitional habitat. The experiment was performed from 8 July to 29 July 2019 in a shallow subtidal area in Pialassa Baiona (Italy), a lagoon characterized by mixing regimes dominated by the tide. The benthic community was isolated using cylinders 15,5Cm x 20Cm size. Hypoxic conditions were imposed by covering the treated cylinders with a black plastic bag while control cylinders were left uncovered. We created 4 different timing regimes of hypoxia by manipulating both the duration of hypoxia (4 or 8 days) as well as the ratio between the duration of subsequent periods of hypoxia and the duration of a normoxic period between subsequent hypoxic events (D4R3/2, D8R3/2). At the end of each experimental trial, the benthic communities within each pot were retrieved, sieved in the field and subsequent analyzed in the laboratory where organisms were identified and counted. Results showed that benthic organism were generally negatively affected by hypoxic stress events. As expected, longer hypoxic events caused a stronger decrease of benthic community abundance. When the hypoxic events were interrupted by the normoxic event there were two different results. If the hypoxic period was too long, the normoxic period didn’t cause a positive recovery effect, and further decline of the benthic community was observed. Conversely normoxia had positive effects if the period of hypoxia was short enough not to compromise the benthic community. This resulted in a statistically significant interaction between the tested factors Duration and Ratio. Amphipods were the most sensitive organisms to hypoxia. We conclude that the effects of hypoxia can be greatly relieved by short normoxic periods if they happen frequently enough.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.