Effects of flooding on coastal vegetation and salt marshes

This thesis examines the effects of flooding on coastal and salt marsh vegetation. I conducted a field experiment in Bellocchio Lagoon to test the effects of different inundation periods (Level 1 = 0.468 or 11.23 hours; Level 2 = 0.351 or 8.42 hours; Level 3 = 0.263 or 6.312 hours; Level 4 = 0.155 or 3.72 hours; Level 5 = 0.082 or 1.963 hours; Level 6 = 0.04 or 0.96 hours) on the growth responses and survival of the salt marsh grass Spartina maritima in summer 2011 and 2012. S. maritima grew better at intermediate inundation times (0,351 hours; 0,263 hours, 0,115 hours; 0,082 hours), while growth and survival were reduced at greater inundation periods (0,468 hours). The differences between the 2011 and 2012 experiment were mainly related to differences in the initial number of shoots (1 and 5, respectively in 2011 and 2012). In the 2011 experiment a significant lower number of plants was present in the levels 1 and 6, the rhizomes reached the max pick in level 4, weights was major in level 4, spike length reached the pick in level 3 while leaf length in level 2. In the 2012 experiment the plants in level 6 all died, the rhizomes were more present in level 3, weights was major in level 3, spike length reached the pick in level 3, as well as leaf length. I also conducted a laboratory experiment which was designed to test the effects of 5 different inundation periods (0 control, 8, 24, 48, 96 hours) on the survival of three coastal vegetation species Agrostis stolonifera, Trifolium repens and Hippopae rhamnoides in summer 2012. The same laboratory experiment was repeated in the Netherlands. In Italy, H. rhamnoides showed a great survival in the controls, a variable performance in the other treatments and a clear decrease in treatment 4. Conversely T. repens and A. stolonifera only survive in the control. In the Netherlands experiment there was a greater variability responses for each species, still at the end of the experiment survival was significantly smaller in treatment 4 (96 h of seawater inundation) for all the three species. The results suggest that increased flooding can affect negatively the survival of both saltmarsh and coastal plants, limiting root system extension and leaf growth. Flooding effect could lead to further decline and fragmentation of the saltmarshes and coastal vegetation, thereby reducing recovery (and thus resilience) of these systems once disturbed. These effects could be amplified by interactions with other co-occurring human impacts in these systems, and it is therefore necessary to identify management options that increase the resilience of these systems.

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.