Fire is the most frequent disturbance in the Ericaceous Belt ( ca 3000–4300 m.a.s.l.), one of the most important plant communities of tropical African mountains. Through resprouting after fire, Erica establishes a positive fire feedback under certain burning regimes. However, present-day human activity in the Bale Mountains of Ethiopia includes fire and grazing systems that may have a negative impact on the resilience of the ericaceous ecosystem. Current knowledge of Erica –fire relationships is based on studies of modern vegetation, lacking a longer time perspective that can shed light on baseline conditions for the fire feedback. We hypothesize that fire has influenced Erica communities in the Bale Mountains at millennial time-scales. To test this, we (1) identify the fire history of the Bale Mountains through a pollen and charcoal record from Garba Guracha, a lake at 3950 m.a.s.l., and (2) describe the long-term bidirectional feedback between wildfire and Erica, which may control the ecosystem's resilience. Our results support fire occurrence in the area since ca 14 000 years ago, with particularly intense burning during the early Holocene, 10.8–6.0 cal ka BP. We show that a positive feedback between Erica abundance and fire occurrence was in operation throughout the Lateglacial and Holocene, and interpret the Ericaceous Belt of the Ethiopian mountains as a long-term fire resilient ecosystem. We propose that controlled burning should be an integral part of landscape management in the Bale Mountains National Park.

Knowledge coproduction that draws on local and scientific knowledge presents opportunities for more holistic understanding of environmental change. We describe our use of a multiple-evidence based approach to investigate the causes and consequences of environmental change in a community-protected grassland and its surrounding landscape in the Ethiopian highlands. We explore the interaction of biophysical change (precipitation and vegetation) and social change (political and management institutions), and discuss potential impacts for ecosystem service provisioning. We quantified current distributions of locally defined land use/cover classes using a supervised classification, with an overall accuracy of 87.1%. Local community members then described and ranked the ecosystem services associated with each land class according to their perceived importance for society. Vegetation and precipitation changes were assessed using satellite time series beginning in the early 1980s, while local narratives describe changes back to the 1970s. The knowledge coproduction process brought together ethnographic and remote sensing approaches, revealing both complementary and contradictory findings across knowledge systems. Results with high agreement across knowledge systems clarify and reinforce understanding of certain threats and changes to the area, such as the rapidly declining native forests, the disappearing belg rainy season (p = 0.01), and the impact of insecure land tenure on natural resource extraction. Compelling areas of disagreement point to topics in need of further investigation, including increased attention to the spatial and temporal variability of change across a seemingly homogeneous cultural landscape, and the process of shrub encroachment into the protected grassland.

The aim of this research is to investigate the patterns of vascular plant species richness, diversity, and distribution along an elevation gradient in the Abune Yosef mountain range, Ethiopia. Preferential systematic sampling was employed to collect vegetation and environmental data along the elevation gradient. We found that plant species richness declines monotonically from low to high elevations. Specifically, vascular plant species richness and diversity were lower in the Afroalpine grassland (high elevation) than in the Dry evergreen Afromontane forest and Ericaceous forest (low elevations). In contrast, endemic vascular plant richness was significantly higher in the Afroalpine grassland than in the Dry evergreen Afromontane forest and Ericaceous forest. Elevation showed a significant impact on the richness, diversity, and endemism of vascular plants. According to Sørensen's coefficient, the similarity between Dry evergreen Afromontane forest and Ericaceous forest vegetation types is higher (32%) than the similarity between Ericaceous forest and Afroalpine grassland (18%). Only 5% similarity was recorded between the Dry evergreen Afromontane forest and Afroalpine grassland. Growth forms showed different elevational richness patterns. Trees and liana increased monotonically up to 3300 m. Shrub and herb richness patterns followed a hump-shaped and inverted hump-shaped pattern along the elevation gradient. The elevation patterns of vascular plant species richness, diversity, and growth form in the present study may be attributed to differences in management intensity, spatial heterogeneity, microclimatic variations, and anthropogenic disturbances.

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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.

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Abstract. Tropical mountains and highlands in Africa are under pressure because of anthropogenic climate and land-use change. To determine the impacts on the afro-alpine environment and to assess the potential socio-economic consequences, the monitoring of essential climate and environmental variables at high elevation is fundamental. However, long-term temperature observations on the African continent above 3000 m are very rare. Here we present a consistent multiannual dataset of hourly ground temperatures for the Bale Mountains in the southern Ethiopian Highlands, which comprise Africa's largest tropical alpine area. The dataset covers the period from January 2017 to January 2020. To characterise and continuously monitor the mountain climate and ecosystem of the Bale Mountains along an elevation gradient from 3493 to 4377 m, ground temperature data loggers have been installed at seven sites at 2 cm depth; at four sites at 10 cm depth; and at five sites at 2, 10, and 50 cm depth. The statistical analysis of the generated time series reveals that ground temperatures in the Bale Mountains are subject to large daily fluctuations of up to 40 ∘C and minor seasonal variations on the order of 5 to 10 ∘C. Besides incoming short-wave radiation, ground moisture, and clouds at night, slope orientation and the type of vegetation coverage seem to be the main factors controlling daily and seasonal ground temperature variations. On the central Sanetti Plateau above 3800–4000 m, the mean annual ground temperature ranges from 9 to 11 ∘C. However, nocturnal ground frost down to a depth of 5 cm occurs frequently during the dry season from November to February. At the five sites where ground temperature is measured at three depths, the monitoring will be continued to trace long-term changes. To promote the further use of the ground temperature dataset by the wider research community dealing with the climate and geo-ecology of tropical mountains in eastern Africa, it is made freely available via the open-access repository Zenodo: https://doi.org/10.5281/zenodo.6047457 (Groos et al., 2022).