The relationship between vegetation and modern pollen assemblages on Mount Paggeo (NE Greece)

In this study, we investigated the relationship between vegetation and modern-pollen rain along the elevational gradient of Mount Paggeo. We apply multivariate data analysis to assess the relationship between vegetation and modern-pollen rain and quantify the representativeness of forest zones. This study represents the first statistical analysis of pollen-vegetation relationship along an elevational gradient in Greece. Hence, this paper improves confidence in interpretation of palynological records from north-eastern Greece and may refine past climate reconstructions for a more accurate comparison of data and modelling. Numerical classification and ordination were performed on pollen data to assess differences among plant communities that beech (Fagus sylvatica) dominates or co-dominates. The results show a strong relationship between altitude, arboreal cover, human impact and variations in pollen and nonpollen palynomorph taxa percentages.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

Classification of plant communities, structure and diversity of forests in Acre, Brazil.

2016

The flora and vegetation of rocky outcrops in three municipalities in the northern region of Ceará, Brazil: phytosociological characterization

This study aims to identify the flora and vegetation of rocky outcrops of low altitude and confined in the municipalities of Sobral, Groaíras and Santa Quitéria (Ceará state, Brazil), to propose a phytosociological classification for the xerophilous communities. We selected five stations in areas with high proportion of bare rock (> 80%), and the field work were conducted in March 2014 and 2015 respectively (3º 56’ S and 40º 23’ W, 4º 01’ S and 40º 05’ W, 4º 07’’ S and 40º 08’ W, 4º 09’ S and 40º 09’ W and 4º 03’ S and 40º 00’ W). Floristic relevés were made following the Braun-Blanquet classic sigmatist method. The minimum areas of the floristic relevés vary between 8 e 16 m². All the plant species growing in cracks, crevices and vegetation "spots" that can be found in these habitats were identified. The classification of the relevés was made through the Twinspan. The floristic list is composed of 89 species, distributed in 61 genera and 29 families. Fabaceae was the most representative in species richness, 20 species, followed by Poaceae (10 spp.), Euphorbiaceae (7 spp.) and Convolvulaceae (6 spp.). 22 Brazilian endemisms have been identified. Based in the phytosociological analysis and in the classification results we identified five groups and two communities can be clearly distinguished: community of Pilosocereus gounellei FA.C.Weber) Byles & Rowley and Encholirium spectabile Mart. ex Schult. & Schult.f. and the community of Crateva tapia L. and Combretum leprosum Mart..

Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian Semiarid region, for use in Dynamic Global Vegetation Models.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga