Correction to: Satellite Images Combined with Field Data Reveal Negative Changes in the Distribution of Babassu Palms after Clearing off Amazonian Forests.

The original article has been corrected.

Satellite Images Combined with Field Data Reveal Negative Changes in the Distribution of Babassu Palms after Clearing off Amazonian Forests.

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.

Mapping Artisanal and Small-Scale Gold Mining in Senegal Using Sentinel 2 Data.

Artisanal and small-scale gold mining (ASGM) represents a significant economic activity for communities in developing countries. In southeastern Senegal, this activity has increased in recent years and has become the main source of income for the local population. However, it is also associated with negative environmental, social, and health impacts. Considering the recent development of ASGM in Senegal and the difficulties of the government in monitoring and regulating this activity, this article proposes a method for detecting and mapping ASGM sites in Senegal using Sentinel 2 data and the Google Earth Engine. Two artisanal mining sites in Senegal are selected to test this approach. Detection and mapping are achieved following a processing pipeline. Principal component analysis (PCA) is applied to determine the optimal period of the year for mapping. Separability and threshold (SEaTH) is used to determine the optimal bands or spectral indices to discriminate ASGM from other land use. Finally, automatic classification and mapping of the scenes are achieved with support vector machine (SVM) classifier. The results are then validated based on field observations. The PCA and examination of spectral signatures as a function of time indicate that the best period for discriminate ASGM sites against other types of land use is the end of dry season, when vegetation is minimal. The classification results are presented as a map with different categories of land use. This method could be applied to future Sentinel scenes to monitor the evolution of mining sites and may also be extrapolated to other relevant areas in the Sahel.

[Incidence of isolation and antibiotic resistance of E. coli responsible for urinary infections outside hospitals, in specialized hospitals and in general hospitals]. / Fréquences d'isolement et résistance aux antibiotiques des E. coli responsables d'infections urinaires en ville, en centre hospitalier spécialisé et centre hospitalier général.

E. coli is the agent most frequently isolated in urinary infection. In 1982, rates of E. coli isolation were 87% in outpatient laboratories, 63% in general hospitals and 41% in specialized hospitals. Susceptibility to ampicillin was less frequent in outpatients (43%) than in hospitalized patients (67%). In both, isolated strains were susceptible to the major urinary antiseptics ( furans , nalidixic acid, pipemidic acid) and even more so to aminoglycosides. Resistance to beta-lactams was compared in outpatients (1981) and general hospital patients (1982):TEM plasmid resistance was found in 72% and 57% of strains respectively. Resistance to quinolones was unremarkable for all strains studied except for one NALs PIPr phenotype strain recovered from an outpatient.