In Jordan, Salvia ceratophylla L. is traditionally used in the treatment of cancer, microbial infections, and urinary disorders. This study aimed: (1) to chemically characterize S. ceratophylla essential oil (EO) from South Jordan, by gas chromatography (GC) and gas chromatography-mass spectrometry (GC–MS); and (2) to evaluate in vitro the cytotoxic, anti-inflammatory, and antiprotozoal activities of the EO, it’s predominant components, and the hexane (A), ethyl acetate (B), methanol (C) and crude-methanol extracts (D). The analysis revealed that the EO has 71 compounds, with linalool (54.8%) as main constituent. Only the hexane extract (A) showed some cytotoxic activity against SK-MEL, KB, BT-549, SK-OV-3, LLC-PK1 and VERO cells lines with IC50 between 60 and > 100 µg/mL. The EO inhibited NO production (IC50 90 µg/mL) and NF-κB activity (IC50 38 µg/mL). The extracts A, B, and D inhibited NO production and NF- κB activity with IC50 between 32 and 150 µg/mL. Linalool considerably inhibited NO production (IC50 18 µg/mL). The extracts tested did not exhibit antileishmanial activity. Regarding antitrypanosomal activity, the EO exhibited significant results with IC50 2.65 µg/mL. In conclusion, Jordan S. ceratophylla EO represents a rich source of linalool and bears a promising therapeutic potential for further antitrypanosomal drug development.

Invasive plant species (IPS) affect people’s livelihoods and well-being by providing both benefits and costs in different contexts. The objective of this study was to investigate the impact of Prosopis juliflora invasion on land cover change using ground survey and satellite sensor data derived from Landsat ETM+. The study was conducted at Sweimeh, Jordan Valley, between 1999 and 2017. The overall classification accuracy of remotely sensed data was 86% for 1999 and 80% for 2017. Accordingly, a remote sensing approach has the potential to assess land change/cover and aid in monitoring the IPS, specifically Prosopis invasion. Change detection analysis of Landsat classes (i.e., 1999 and 2017) showed that bare soil, urban, and water surface areas decreased by 6%, 11%, and 3%, respectively. Conversely, the vegetation class (i.e., IPS and native plants) increased by 20%. Ground surveys in 1999 and 2017 showed that the average vegetation area in Sweimeh invaded by Prosopis was approximately 60% in 1999 and 70% in 2017. Accordingly, the total estimated area invaded by P. juliflora at Sweimeh (2106 ha) in 1999 was approximately 92 ha, while Prosopis coverage in the same region was approximately 413 ha in 2017. The high emergence rate, the adaptation to high temperatures and low precipitation as well as governmental regulations which restrict the removal of trees, including IPS, were the main factors that prompted the extreme P. juliflora invasion in the Jordan Valley. The high invasion rate has led to a reduction in native species, including Tamarix spp., and dried up five natural water springs in the area. Overall, a monitoring plan should be applied to control the invasion problem by Prosopis in the valley. In addition, the conservation regulations that deal with IPS should be revised to mitigate the IPS risk.

In many countries, including Jordan, the updating of vegetation maps is required to aid in formulating development and management plans for agriculture, forest, and rangeland sectors. Remote sensing data contributes widely to vegetation mapping at different scales by providing multispectral information that can separate and identify different vegetation groups at reasonable accuracy and low cost. Here, we implemented state-of-the-art approaches to develop a vegetation map for Jordan, as an example of how such maps can be produced in regions of high vegetation complexity. Specifically, we used a reciprocal illumination technique that combines extensive ground data (640 vegetation inventory plots) and Sentinel-2 satellite images to produce a categorical vegetation map (scale 1:50,000). Supervised classification was used to translate the spectral characteristics into vegetation types, which were first delimited by the clustering analyses of species composition data from the plots. From the satellite image interpretation, two maps were created: an unsupervised land cover/land use map and a supervised map of present-day vegetation types, both consisting of 18 categories. These new maps should inform ecosystem management and conservation planning decisions in Jordan over the coming years.

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