Distribution and conservation of Aniba Aubl. (Lauraceae Jussieu) species in Brazil

Abstract: This study conducts a biogeographical review of Aniba in Brazil, including its actual and potential distribution, and a review on the species conservation status. The potential distribution of each Aniba species was modeled using the Brazilian Plants and Fungi Biogeography system, which is interconnected with the SpeciesLink network. A consensus model based on up to five algorithms was used to model the potential distribution of each species. The endemism, conservation status and rarity of each species in Brazil were also analyzed. A total of 3059 records of 30 Brazilian Aniba species were found. In total, 16.1% of the records were excluded because of the lack of valid names, and 53.4% were excluded because of the lack of georeference and name of the person who identified the record. The consensus model showed good results for species with 20 or more pixels. The other species had many errors, and their models could only be used to determine new areas for collections. Nine species were endemic to Brazil, and only three species showed no indicator of rarity. The geographical distribution of Brazilian Aniba species shows a predominantly Amazonian pattern. Only four species are not actually found in the Amazon. Some Amazonian species may also be found in Atlantic Forest areas, and many other species have the potential to live there. Our results indicate that only three species have no conservation problems, whereas 14 species have conservation problems, and 13 other species require further population studies to be best evaluated.

Hydro-edaphic conditions defining richness and species composition in savanna areas of the northern Brazilian Amazonia

BACKGROUND

Studies on plant communities in the Amazon have reported that different hydro-edaphic conditions can affect the richness and the species composition of different ecosystems. However, this aspect is poorly known in the different savanna habitats. Understanding how populations and plant communities are distributed in these open vegetation areas is important to improve the knowledge about which environmental variables influence the occurrence and diversity of plants in this type of regional ecosystem. Thus, this study investigated the richness and composition of plant species in two savanna areas of the northern Brazilian Amazonia, using the coverage (%) of the different life forms observed under different hydro-edaphic conditions as a structural reference.

NEW INFORMATION

We report 128 plant species classified in 34 botanical families distributed in three savanna habitats with different levels of hydro-edaphic restrictions. In this study, the habitats are conceptually presented and they integrate environmental information (edaphic factors and drainage type), which determines differences between floristic composition, species richness and coverage (%) of plant life forms.

Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images

High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale.

Cartographier le carbone stocké dans la végétation : perspectives pour la spatialisation d¿un service écosystémique

Les grands programmes internationaux d'observation des écosystèmes, tels que le Millenium Ecosystem Assessment (Mea), puis Redd (Réduction des émissions liées à la déforestation et à la dégradation des forêts) et Redd+, préconisent le développement des approches permettant de quantifier et de spatialiser les services écosystémiques afin de mettre en oeuvre des pratiques et des politiques de gestion environnementale plus adaptées. La cartographie des services écosystémiques apparaît ainsi comme un outil majeur des espaces à forts enjeux environnementaux. Cependant, elle souffre encore de certaines limitations. C'est le cas du stock de carbone dans la biomasse végétale. À l'échelle d'une localité d'Amazonie brésilienne de 175 km², cette fonction écologique a été cartographiée avec une résolution spatiale de 30 x 30 m. Afin de quantifier ces stocks, des mesures de biomasse arborée et arbustive au sein de 45 " points " et des données géographiques obtenues par télédétection sont mises en jeu. Pour cela, deux méthodes statistiques sont testées : l'arbre de décision et la régression linéaire multiple. Les résultats statistiques de chacune de ces méthodes sont présentés, permettant d'en comprendre les intérêts et les inconvénients. La qualité d'ajustement de ces modèles est testée. Si l'arbre de décision décrit mieux le rôle des variables explicatives, la régression linéaire multiple permet une prédiction beaucoup plus efficace. Elle rend alors davantage compte de la variabilité spatiale au sein de chaque type d'occupation du sol. Cette méthode fait apparaître à l'échelle de la ferme des phénomènes spécifiques au territoire étudié. Cela permet de retranscrire simplement le résultat d'un processus écologique tout en le mettant en relation avec les activités anthropiques. Cette étude permet donc d'illustrer l'importance des choix méthodologiques afin d'obtenir la cartographie d'un processus.