Name: Guerreiro R

Biodeserts supervisors: Boratyński ZMartínez-Freiría F

Title: Biogeography in Northwestern Africa: distributions and ecological niches of Gerbillus rodents

Institution: University of Porto

Status: Completed




North Africa is a very wide arid region, often forgotten in biogeography studies due to low accessibility and socio-political problems that hinder fieldwork. However, that region is very relevant to study biogeography patterns, having been shaped by dramatic climatic shifts and containing organisms adapted to very extreme environments. Particularly, the western coast of North Africa seems to be very interesting to study biogeography, due to the influence from the Atlantic Ocean, complex topography and history of changing sea level. In this region, and following the trend of increasingly affordable molecular identification of species, new data is accumulating for several species of Gerbillus rodents. Gerbillus distributions in North Africa appear to overlap more than previously thought, which raises questions of how and where species coexist, and why some areas have a higher species richness than others. It was the main aim of this study to predict suitable areas for Gerbillus species and possible areas of coexistence, as well as to understand the topo-climatic and habitat drivers shaping their distributions.
This thesis combines distribution data for 12 Gerbilllus species spanning over North Africa, most of it with molecular confirmation of species’ identification through barcoding. These species (G. amoenus, G. campestris, G. gerbillus, G. henleyi, G. hesperinus, G. hoogstraali, G. nancillus, G. nigeriae, G. occiduus, G. pyramidum, Gerbillus sp., G. tarabuli) are here subject to a comparative study of their topo-climatic and habitat drivers by using Geographical Information Systems (GIS) and Ecological Niche-based Modeling (ENM). The species reactions to climatic drivers were used to project their distribution to the past climates of Middle Holocene, Last Glacial Maximum and Last Interglacial. Stable climatic areas were accessed for each species by overlapping their distribution projections of different periods. In a similar way, potential species richness was accessed by overlapping the niche models of all species. The topo-climatic and habitat niches of the species were compared with niche overlap, identity and background tests, striving to find any connection between niche overlap and phylogenetic relatedness, asking if the niches are conserved between species.
The results of this work show suitable areas for each species in North Africa, which together with novel geographical locations provide an update for species distributions. The analysis of climatic drivers revealed that temperature variables are generally the most important predictors of distributions. Especially large diurnal and annual temperature ranges as well as low minimum temperatures on the coldest month constrain niches. Precipitation played a role differentiating species, as some Gerbillus avoid areas with relatively high precipitation levels while others avoid areas with almost null precipitation levels. Somewhere in between (intermediate precipitation levels) appears to be the highest potential species richness of Gerbillus. Projections to the humid Middle Holocene revealed insignificant suitability distribution changes, as temperature ranges in this period were similar to current day. Suitability distributions were generally smaller in the colder Last Glacial Maximum and changed substantially in the Last Interglacial, a period with smaller temperature ranges that should have benefited all species. When concerning climatic, topo-climatic and habitat variables, niche overlap between species was observed to correspond to geographical overlap suggesting adaptation to local conditions. However, the niches of the species appear to be relatively similar, suggesting niche conservatism. Relatively high niche conservatism predicts allopatry as the main speciation engine of the genus in the studied region. The species appear thus to select similar environmental variables, even when different geographic distributions expose them to different available environmental variation.