Initial oak regeneration responses to experimental warming along microclimatic and macroclimatic gradients.

Quercus spp. are one of the most important tree genera in temperate deciduous forests in terms of biodiversity, economic and cultural perspectives. However, natural regeneration of oaks, depending on specific environmental conditions, is still not sufficiently understood. Oak regeneration dynamics are impacted by climate change, but these climate impacts will depend on local forest management and light and temperature conditions. Here, we studied germination, survival and seedling performance (i.e. aboveground biomass, height, root collar diameter and specific leaf area) of four oak species (Q. cerris, Q. ilex, Q. robur and Q. petraea). Acorns were sown across a wide latitudinal gradient, from Italy to Sweden, and across several microclimatic gradients located within and beyond the species' natural ranges. Microclimatic gradients were applied in terms of forest structure, distance to the forest edge and experimental warming. We found strong interactions between species and latitude, as well as between microclimate and latitude or species. The species thus reacted differently to local and regional changes in light and temperature ; in southern regions the temperate Q. robur and Q. petraea performed best in plots with a complex structure, whereas the Mediterranean Q. ilex and Q. cerris performed better in simply structured forests with a reduced microclimatic buffering capacity. The experimental warming treatment only enhanced height and aboveground biomass of Mediterranean species. Our results show that local microclimatic gradients play a key role in the initial stages of oak regeneration; however, one needs to consider the species-specific responses to forest structure and the macroclimatic context.

A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well.