Arid environments are characterized by rare rain events that are highly variable, as a result of which plant populations often exhibit episodic recruitment and mortality dynamics. However, direct records and observations of such events are rare because of the slow development of woody species. In this study, we described how a decrease in annual precipitation affected acacia tree population dynamics in two hydrological regime types: small wadis and salt flats. This study combines 15 years of continuous, yearly field monitoring of individual acacia trees and data from a historical Corona satellite image, which has extended the time scope of the research. Results indicate that the annual mortality of acacia trees in small wadis reflects the cumulative effective rain events in the preceding five years, whereas the population on the salt flats was not affected by annual rainfall fluctuations. Moreover, in small wadis, rain events of less than 8 mm did not increase acacia tree survival rates. The mortality pattern and dynamics of each plot was unique, suggesting unsynchronized mortality and recruitment episodes on a regional scale. Mortality in all plots was documented both in “old” trees (i.e., recognized in 1968) and “new” trees (not recognized in 1968), but varied highly between plots. More than 50% of the dead trees recorded at the sites had died during the previous dry period (2000–2010). Combining field monitoring and historical satellite image data provided a unique database of acacia population dynamics. This record revealed the response of the acacia population to climate fluctuations and a period of episodic mortality.

Previous research investigating the under-representation of women in science and technology fields has identified various causes. These include, a lack of inspiring female role-models, limited exposure of girls to science, technology, engineering, and mathematics (STEM) subjects, gender-biased stereotypes, and preferences for different learning styles between genders. Dedicated to the ideas of women and space, the “She Space” research project for high school girls was a joint effort of the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University in the Negev and Beit Yatziv. The participants included 20 high-school aged female students and a predominantly female staff of up to eight university researchers and advanced degree students. The goal of this project was to advance and support female students engaging with various scientific fields and, in particular, the field of space science. The project emphasized the quality and development of the research process and used project-based learning to help participants learn to use a research-based approach when encountering challenging scientific concepts or subjects. This, together with active learning and teamwork was set as the educational framework to meet the different learning styles and motivational needs of girls. Furthermore, special attention was given to the suppression of gender stereotypes by 1) introducing women role models 2) overcoming self-induced prejudices related to STEM abilities by introducing new and unknown subjects (remote sensing), about which participants lack preconceptions. Using participant surveys, we found that self-reported confidence with and interest in STEM subjects increased after the project. We also found that participants’ feelings about participating in an all-female program did not noticeably change after the program. However, the vast majority (87%) of participants did report that having a majority female staff was very important to them.

Monitoring vegetation dynamics in hyper-arid zones is important because any decrease in the already sparse vegetation cover in these areas could considerably affect the entire ecosystem. The new generation of high spatial resolution satellite (HSR) sensors is suitable for monitoring trees in arid regions because of the distinct and separate objects that trees represent in these environments. The main limitation of modern HSR sensors is the lack of a historical archive that would otherwise enable meaningful landscape change detection, especially in arid regions where tree population dynamics are naturally very slow. This study uses spatial analysis to gain information regarding the long- and short-term dynamic processes affecting the acacia tree population in Wadi Ktora, in the southern Arava Valley, Israel. The data is extracted from a single HSR aerial photograph composed of three spectral bands in the visible and infrared spectrum (green, red, and near infrared).

A map of individual acacia trees that is extracted from a colour infrared aerial photograph of Wadi Ktora from 2010 enables the examination of spatial distribution patterns for both tree size and foliage health. Tree size distribution is used as an indicator of long-term (decades) hydrologic spatial processes affecting the acacia population. The tree health distribution is used as an indicator for short-term (months to a few years) hydrologic spatial processes, such as the paths of recent flash floods events. Comparing the distributions of tree size and normalized difference vegetation index (NDVI) enables differentiation between the long-term and short-term processes that brought the population to its present state.

Using spatial statistic grouping, the distribution of the trees in the wadi (ephemeral stream) is divided into three distinct categories: (1) large trees with high NDVI values, (2) large trees with low NDVI values, and (3) small trees with medium NDVI values. Using the resulting classification, we divided the wadi into three sections, each representing a unique combination of long- and short-term hydrologic processes affecting the acacia trees. We suggest that the lack of spatial correlation between tree size and health status is a result of spatio-temporal changes in the water supply.