Remote sensing‐supported mapping of the activity of a subterranean landscape engineer across an afro‐alpine ecosystem

Abstract

Subterranean animals act as ecosystem engineers, for example, through soil perturbation and herbivory, shaping their environments worldwide. As the occurrence of animals is often linked to above-ground features such as plant species composition or landscape textures, satellite-based remote sensing approaches can be used to predict the distribution of subterranean species. Here, we combine insitu collected vegetation composition data with remotely sensed data to improve the prediction of a subterranean species across a large spatial scale. We compared three machine learning-based modeling strategies, including field and satellitebased remote sensing data to different extents, in order to predict the distribution of the subterranean giant root-rat GRR, Tachyoryctes macrocephalus, an endangered rodent species endemic to the Bale Mountains in southeast Ethiopia. We included no, some and extensive fieldwork data in the modeling to test how these data improved prediction quality. We found prediction quality to be particularly dependent on the spatial coverage of the training data. Species distributions were best predicted by using texture metrics and eyeball-selected data points of landscape marks created by the GRR. Vegetation composition as a predictor showed the lowest contribution to model performance and lacked spatial accuracy. Our results suggest that the time-consuming collection of vegetation data in the field is not necessarily required for the prediction of subterranean species that leave traceable above-ground landscape marks like the GRR. Instead, remotely sensed and spatially eyeball-selected presence data of subterranean species could profoundly enhance predictions. The usage of remote sensing-derived texture metrics has great potential for improving the distribution modeling of subterranean species, especially in arid ecosystems.

Topographic barriers drive the pronounced genetic subdivision of a range‐limited fossorial rodent

“…Our landscape genetic findings align with recent satellite‐based predictions of giant‐root rat distribution, which indicated the species' distribution can be explained by texture metrics of the landscape, i.e. factors that characterize topographic variation across the landscape (Wraase et al., 2022).…”

“…Their primary food resource is Alchemilla (Yaba et al., 2011). The vegetation index, which is based on remotely‐derived satellite data, may not distinguish its spectral signal from other preferred plants (Wraase et al., 2022). Additionally, the giant root‐rat requires soil layers of approximately 50 cm in depth to engineer burrow systems and for thermoregulation (Sillero‐Zubiri et al., 1995; Šumbera et al., 2020).…”

Topographic barriers drive the pronounced genetic subdivision of a range-limited fossorial rodent

“…These barriers to dispersal and the fossorial lifestyle of the giant root-rat limiting the species' ability to traverse pronounced topographic structures, presumably caused the strong genetic subdivision of the species. Our landscape genetic result is in agreement with recent satellite-based mapping of the giant-root rat's distribution, which found that the texture of the landscape is the most critical factor in explaining the species' range (Wraase et al, 2022) In addition to slope and elevation, the pronounced subdivision observed in giant root-rats may also have been reinforced by glacial extents during the Late Pleistocene. The Bale Mountains are currently ice-free, but the Sanetti Plateau, the south region, was glaciated between ~42,000 to 16,000 years ago (kya) (Figure 1C; Groos et al, 2021;Ossendorf et al, 2019).…”

“…Their primary food resource is Alchemilla (Yaba et al, 2011). The vegetation index, which is based on remotely-derived satellite data, may not distinguish its spectral signal from other nonpreferred plants (Wraase et al, 2022). Additionally, the giant root-rat requires soil layers of approximately 50 cm in depth to engineer burrow systems and for thermoregulation (Sillero-Zubiri et , 1995; Šumbera et al, 2020), and while soil depth and moisture are likely correlated (deeper soil can store more water, Tromp-van Meerveld & McDonnell, 2006), soil moisture as a proxy for soil availability may not capture areas of sufficient soil depth.…”

Human activities modulate reciprocal effects of a subterranean ecological engineer rodent, Tachyoryctes macrocephalus, on Afroalpine vegetation cover

“…Through this reciprocal effect, giant root-rats' engineering does not only affect vegetation but also positively affects the giant root-rats themselves, because the reduction in vegetation cover they cause eventually creates higher quality habitat. This supposition holds true, in the light of findings of previous studies (Miehe & Miehe, 1994;Šklíba et al, 2017;Wraase et al, 2022;Yalden, 1975) that giant root-rats' own long-term burrowing activity plays an important role in their habitat selection. Despite the significant effects of giant rootrat burrow density on vegetation cover, we found a nonsignificant effect on plant species richness, which is in line with finding of our previous study on giant root-rat (Asefa et al, 2022), as well as studies on other rodents elsewhere (e.g.…”