Understanding landscape resilience by changes at fine scale

It is an important issue to understand how an ecosystem reacts to different disturbances and to quantify its adaptation and self-regulation ability. In the last decades, a concept attempting to characterize these characteristics is that of resilience (Cumming, 2011). An important issue related to the fragile environmental equilibrium is the emerging infrastructure of the new renewable energy sources. It is therefore crucial to understand how this type of infrastructure can affect the environmental equilibrium and how ecosystems react and how disturbances can be mitigated. An issue that needs to be investigated refers to the impact on wind turbines on vegetation structure and soil properties at local scale.
The general hypothesis tested in this analyse is that the microclimate generated by wind farm could affect the vegetation and the soil microbiota. More precisely, we will focus on resilience of vegetation and soil microbiota in the context of the local weather conditions induced by wind farms. Many study confirm that wind farms affect near surface air temperature, humidity and CO2 flows between the land surface and the atmosphere (Petersen et al., 1998; Baidya Roy et al., 2004; Baidya Roy & Traiteur, 2010). It is expected that these changes impact vegetation and soil at a fine scale. Our research question is: could changes in microclimatic and microbiota conditions (due to wind turbines) affect vegetation development (growth, patterning)?
We chose two wind farms situated in the SW Carpathians. In both sites we will implement the same design, consisting of two transects (turbine and control transect). In each transect, plots will be considered and certain parameters regarding meteorological data, vegetation and soil. On the other hand we realize: (i) an inventory of plant species; (ii) identification of indicator species as well as of rare species, which react / reflect precisely any changes of environmental conditions (soil humidity, soil trophicity, etc.); (iii) monitoring along TT and TC for identifying aridity trends of pastures (having impact on biomass and forage production and quality).
We collected in situ information about the phytocoenosis structure using four transects and made an inventory containing 98 species. Along the transects we had 16 sampling points that captured 43 species. The data collected showed that the phytocoenosis structure of the both sites is quite similar, but we identified some differences (Figure 1). The transects within the proximity of the wind farm have 32 species, that are not found in the control transects and they lack four species that are present in the control transects (Figure 2). For understanding ecological indicators (Table 1) we collected microclimate data regarding the air temperature and humidity that showed slight differences between the microclimates within the two sites, which emphasizes the fact that the phytocoenosis structure is different in the presence of the wind farm.