Savanna vegetation maintains its openness and its diverse plant composition because of frequent fire events; however, when these are suppressed, encroachment is caused by increases in the tree density. In the neotropical savanna (cerrado of Brazil), typical forest trees are invading savanna areas, altering abiotic conditions and affecting the persistence of their exclusive species. Here we studied changes in abiotic conditions, species richness and diversity of a non-arboreal community (herbs, vines, grasses, subshrubs and shrubs) in a gradient of encroachment at a site where fire has been suppressed for more than 50 years in south-eastern Brazil. Encroached communities were more shaded and possessed a wetter and richer soil (higher contents of organic matter and P) compared with the typical savanna. These abiotic changes were related to a less rich and less diverse plant community in encroached savanna compared with typical savanna. The most important abiotic variables driving such changes were photosynthetically active radiation (PAR) reaching the understorey and soil P content: communities with lower species richness and diversity had lower PAR incidence and higher soil P content. Our results suggest that non-arboreal savanna species may be under serious threat of extinction given the expected ecological changes caused by the widespread expansion of forest on the savannas in the absence of fire.

This paper proposes a methodology for plant analysis and identification based on extracting texture features from microscopic images of leaf epidermis. All the experiments were carried out using 32 plant species with 309 epidermal samples captured by an optical microscope coupled to a digital camera. The results of the computational methods using texture features were compared to the conventional approach, where quantitative measurements of stomatal traits (density, length and width) were manually obtained. Epidermis image classification using texture has achieved a success rate of over 96%, while success rate was around 60% for quantitative measurements taken manually. Furthermore, we verified the robustness of our method accounting for natural phenotypic plasticity of stomata, analysing samples from the same species grown in different environments. Texture methods were robust even when considering phenotypic plasticity of stomatal traits with a decrease of 20% in the success rate, as quantitative measurements proved to be fully sensitive with a decrease of 77%. Results from the comparison between the computational approach and the conventional quantitative measurements lead us to discover how computational systems are advantageous and promising in terms of solving problems related to Botany, such as species identification.

In the Brazilian savanna (Cerrado of Brazil), fi re suppression has transformed typical savanna formations (TS) into forested savanna (FS) due to the phenomenon of encroachment. Under encroachment, non-arboreal plants begin to receive less light due to greater tree density and canopy closure. Here we aim to evaluate if leaf anatomical traits of non-arboreal species diff er according to the degree of tree encroachment at the Assis Ecological Station -São Paulo, Brazil. To this end, we evaluated leaf tissue thickness and specifi c leaf area (SLA) in representative non-arboreal species occurring along a gradient of tree encroachment. Leaves of TS species showed a trend towards xeromorphism, with traits reported to facilitate survival under high luminosity, such as thick leaves, thick epidermis and mesophyll, and low SLA. In contrast, FS species exhibited mesomorphic leaves, with thin mesophyll and high SLA, which are able to capture diff use light in denser environments. Th us, non-arboreal understory species with mesomorphic leaf traits should be favored in environments with denser vegetation in contrast to typical savanna species. Th e results suggest that typical non-arboreal savanna species would not survive under tree encroachment due to the low competitiveness of their leaf anatomical strategies in shady environments.

Aim Woody‐plant encroachment is a reality in many savannas worldwide, leading savannas to become replaced by forest ecosystems. As tree density and cover increase, increased shade and litter deposition may suppress the savanna's community of low‐lying plants. By using field manipulation, we tested shading and litter effects, alone and in combination, on the savanna's ground‐layer plant community. We investigated how changes in these environmental factors may affect the composition, structure, and above‐ground biomass in the plant community of a species‐rich Neotropical savanna. Location Savanna patches in the Cerrado, southeastern Brazil. Methods Annual surveys of the herbaceous–shrub layer in a three‐year field manipulation experiment examining shading and litter deposition. Results Shade negatively affected all evaluated parameters, while litter addition had only minor effects. The largest losses of richness, density, and cover occurred in forbs and grasses. Increased shade resulted in a sharp decrease in the above‐ground biomass of monocots. Conclusions Our results show that light is a strong environmental filter for the ground‐layer community. The reductions in grass cover and biomass under shade treatments likely altered ecosystem functioning. Woody encroachment can thus be considered to represent a process that can alter the structure and functioning of savannas. Management interventions should therefore be taken to prevent woody encroachment or mitigate its harmful effects on savanna biodiversity and ecosystem functioning.

The identification of plant species is not a trivial task, since it is carried out by experts and depends on the presence of fruits, flowers and leaves. However, fruits and flowers are not available throughout the year, while leaves are accessible most of the year. In order to assist the specialized work of species identification, methods of texture image analysis are used to extract characteristics from samples of imaged leaves and thus predict the species. Texture image analysis is a versatile and powerful technique able to extract measurements from patterns in the images. Using this technique, recent research has found a close relationship between texture and plant species (da Silva et al., 2015 and2016). Here, we describe the procedure to extract texture features from microscopic images of leaves using Fourier (Cosgriff, 1960;Azencott, 1997;Gonzalez and Woods, 2006). It is important to highlight that other methods for texture extraction can be used as well.This protocol is split into two parts: (A) leaf epidermal dissociation and (B) automatic method for leaf epidermal image analysis.