4. Discussion
Climatic factors are the paramount determinant influencing the spatial
distribution of species on a broad scale (Thuiller et al., 2008).
Consequently, alterations in climate conditions stemming from human
activities can adversely affect species’ future distribution and
survival. Among various ecosystems, arid and semi-arid regions encompass
roughly one-third of the Earth’s surface and exhibit heightened
vulnerability to the evolving climate. To effectively plan and execute
initiatives for biodiversity conservation, it becomes imperative to
forecast the potential habitat range of species and delineate their
spatial patterns under future climate conditions. This is particularly
crucial for the hot and arid Saharo-Sindian ecosystem, characterized by
low resilience. In the study, the task of predicting the impact of
climate change on the spatial distribution of Z. spina-christiand Z. nummularia while also assessing their spatial niche
segregation was undertaken. The findings carry substantial implications
for the conservation of these species (Harris et al., 2006; Ghehsareh
Ardestani et al., 2021).
Top of Form
Our research revealed that variables linked to temperature exerted the
most influence on predicting the spatial range of Z.
spina-christi . In the case of Z. nummularia , the most
influential factors were the precipitation during the coldest quarter,
maximum temperature during the warmest month, and isothermality.
Notably, Ghehsareh Ardestani et al. in (2021) conducted a study in
southern Iran focusing on the distribution of Haloxylon persicumand highlighted the pivotal role played by temperature-related variables
in determining the species’ range. It is worth noting that our findings
diverge from those presented by Ksiksi et al. (2019). According to their
research, the three primary predictors influencing the geographical
distribution of Ziziphus spina-christi in the United Arab
Emirates encompassed precipitation during the coldest quarter, annual
precipitation, and mean diurnal range, accounting for approximately 80%
of the predictions.