When the Amazonian rain forest is cut to create pasture, some of the original vegetal species survive clearing, even expressing their ability to invade agro-systems. It is true of the babassu palm, which can be considered, paradoxically, a natural resource by the "Interstate Movement of Babassu Fruit Breaker Women" or as native weed by land owners-farmers. To manage potential conflict of land uses, we study here the current density of this palm tree in different habitats, based on a combination of field data and remote sensing data. Firstly, we checked that the field survey methodology (i.e., counting free-trunk palm trees over 20 cm in circumference) provides density values compatible with those stemming from satellite images interpretation. We can see then that, a PA-Benfica Brazilian territory revealed an average density of the babassu lower in pastures (2.86 ind/ha) than in the dense forest (4.72 ind/ha) from which they originate and than in fallow land (4.31 ind/ha). We analyze in detail density data repartition in three habitats and we discuss results from the literature on the density of this palm tree versus its resilience at different developmental stages after forest clearing, depending on anthropogenic-or not-factors, including solar radiation, fire, weeding, clear cutting, burying fruit, and competition with forage grass. All these results can be exploited for the design of future management plans for the babassu palm and we think that the linked methodology and interdisciplinary approach can be extended to others palms and trees species in similar problematic issues.

In order to quantitatively analyse the spatial pattern of cacao swollen shoot disease, particularly in cases of re-emergence, three experimental plots were installed in a diseased area of cacao cv. Amelonado in Togo. After thorough cleaning and grubbing, the three plots were planted with less susceptible, hybrid plant material. Twenty years after replanting, a survey of healthy, diseased and dead trees was carried out during 2 consecutive years. Data were analysed using Ripley's functions and join counts analysis. The re-emergence of the disease occurred in patches or foci: following analyses with the two statistical methods, diseased trees and dead trees were found to be clearly aggregated on the three observed plots for the 2 years. The observed progress of the disease was not the same on the three plots and seemed dependent on the disease state of the first year: the higher the attack rate of the first year, the faster the disease progression. The use of less susceptible plants helped keep the land productive for 15 years. In conclusion, uprooting of the first infection focus can extend the life of cacao plots.

The Niger River Niamey flood of 2012: The paroxysm of the Sahelian paradox? During the 2012 monsoon, the Middle Niger River exhibited the highest flood ever registered from the beginning of its monitoring in1929. Large areas were flooded, including parts of the city of Niamey. This flooding was due to the combination of an increase in runoff coefficient observed in the Sahelian basin, linked to soil crusting, and an exceptionally high amount of rainfall. Indeed, it was the highest observed since the beginning of the drought in 1968. Due to the level of damage, policy makers should be made aware of the increase in discharges, which is increasing the risk of flooding.

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.