Understanding how primates adapt their foraging strategies to fluctuating environmental conditions is a central theme in behavioral ecology. The extreme Afro-alpine ecosystem presents a unique setting to test predictions of Optimal Foraging Theory and the Fallback Food Hypothesis due to its severe seasonal shifts in resource availability. This study investigated the dietary composition, seasonal variation, food preferences (dietary selectivity), and foraging plasticity of the Southern Gelada ( Theropithecus gelada obscurus ) in the Abune Yosef Zigit Community Conservation Area, Ethiopia. Using instantaneous scan sampling and vegetation surveys across dry and wet seasons, we recorded 761 feeding records encompassing 25 food items. Forbs dominated the diet (55.7%), followed by grasses (42.7%), and insects (1.6%). Geladas exhibited a consistent bimodal feeding pattern but demonstrated pronounced seasonal niche shifts. In the dry season, they highly expanded their dietary breadth (Shannon H' = 2.31) and relied heavily on underground roots, aligning with fallback food strategies. In the wet season, the dietary niche narrowed (H' = 1.92), with greater reliance on grass blades and young shoots. Electivity indices revealed highly dynamic, context dependent selectivity rather than fixed preferences, with preference rankings shifting between seasons. These findings highlight the remarkable behavioral plasticity of geladas and underscore their ability to dynamically adjust foraging strategies to survive in extreme, highly seasonal environments.
This study investigates the spatial and temporal distribution of copper (Cu) in soils affected by long-term atmospheric emissions from a major copper smelter in the Zlatitsa–Pirdop Valley, Bulgaria. The objective is to assess how industrial activity and subsequent technological changes influenced Cu accumulation patterns over a 48-year period (1973–2021). Soil samples were collected along eastward transects at multiple distances from the smelter and analyzed using standard aqua regia digestion followed by atomic absorption spectrometry (AAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) techniques. Three temporal datasets (1973, 1995 and 2021) were compared to evaluate long-term changes in Cu concentrations and spatial distribution. The results show a pronounced shift in contamination patterns over time. In 1973, Cu concentrations exhibited a clear decrease with distance from the emission source, indicating localized deposition. In contrast, data from 1995 and 2021 reveal a more complex spatial pattern, with persistently elevated Cu levels at greater distances from the smelter. This change reflects modifications in emission release height, atmospheric dispersion conditions, and long-term redistribution processes. The study demonstrates that Cu behaves as a persistent and poorly mobile contaminant in surface soils, with limited natural attenuation over decadal time scales. Despite significant improvements in emission control technologies after industrial privatization, historical deposition continues to dominate current soil contamination levels. The findings highlight the combined role of anthropogenic emissions, valley topography, meteorological conditions, and local geochemical background in controlling heavy metal distribution. This study contributes to a better understanding of long-term soil contamination dynamics in industrial mountain-valley environments and provides a basis for environmental monitoring and risk assessment strategies.
Arisaema schimperianum (Schott) is an underutilized crop grown in the Gamo highlands of Ethiopia. It supports the food security and livelihoods of local people, while its management and utilization constitute an essential component of ethnobotanical knowledge and food culture within local communities. This study was intended to document the indigenous knowledge of local people concerning the production and utilization of the crop and its uses. A mixed sampling strategy was used for data collection: purposive sampling for districts and kebeles, random sampling for household heads, and a combined purposive and snowball sampling approach to select knowledgeable elders for the study. Ethnobotanical data were collected from a total of 357 informants: 318 through semi-structured interviews, 30 through focus group discussions, and nine through key informant interviews. The results revealed that local people recognize the diversity of A. schimperianum landraces and their associated folk names and classify them. Approximately two-thirds of respondents identified landraces based on morphometric attributes; approximately four-fifths cited the plant as a food crop, and a small fraction (13%) cited it as a source of food, ethnomedicine, and ethnoveterinary medicine, while only a small minority (5%) reported it as a source of food and ethnoveterinary medicine. Planting propagules and managing the farm throughout the dormancy period highlighted growers’ tacit ecological knowledge of the plant’s phenology, while intercropping practices revealed environmentally friendly agriculture. Postharvest practices, namely pulverization and fermentation, have been pivotal traditional skills in making the crop nutritious for human consumption. The local community domesticates, manages, and continues to use the crop, which helps preserve local food traditions and biodiversity. The multiple regression output highlighted that sociodemographic factors (age, gender, education level, occupation, marital status, and family size) significantly influenced informants’ local knowledge ( F = 78.507, p < 0.001). Social stigmatization, tedious culinary processes, land-use changes, and lack of promotion have been threatening the sustainability of the crop and associated traditional knowledge.
National parks in Ethiopia face the dual challenge of conserving biodiversity, while sustaining local livelihoods. However, limited empirical evidence exists on how socio-economic, cultural and institutional factors collectively shape community perceptions of conservation policy effectiveness. This study investigates these determinants in Loka Abaya National Park, Sidama Region, Ethiopia, using an integrated framework grounded in Social exchange theory (SET) and the institutional analysis and development (IAD) framework. A mixed-methods approach was employed, combining household surveys (n = 128) with key informant interviews and focus group discussions. Determinants of policy perception were analysed using an ordered logistic regression model. Results reveal that favourable perceptions are driven by higher income, larger farmland size, greater distance from the park, education and involvement in decision-making. Notably, two counter-intuitive findings emerged: prior conflict with park authorities positively predicted favourable perceptions—likely reflecting the visibility of state enforcement—while secure land tenure predicted unfavourable views, possibly due to perceived restrictions on agricultural expansion. Conversely, larger household sizes and negative economic interactions with the Park (driven by widespread resource dependence) significantly predicted unfavourable perceptions. The findings underscore that, without viable alternative livelihoods, restrictive conservation policies exacerbate local vulnerabilities. To reconcile biodiversity goals with human well-being, policy-makers must transition from exclusionary governance to participatory, rights-based co-management. Prioritising equitable benefit-sharing, tenure-sensitive boundary delineation and conservation education are essential to enhancing policy legitimacy and long-term biodiversity outcomes in Ethiopia’s protected areas.
Because they are able to absorb and store atmospheric carbon, mangrove ecosystems help combat climate change. Nevertheless, few studies combining spatial analysis of mangrove carbon stock estimation with estimation of the mangrove area required to offset anthropogenic emissions at the subdistrict level have been conducted in rapidly developing coastal regions. This research aimed to estimate the mangrove area needed to offset anthropogenic carbon emissions in the coastal areas of Gresik Regency, East Java Province, Indonesia. Transects and 10 × 10 m plots were used for field surveys conducted in seven coastal subdistricts. DBH measurements of mangroves were fitted to species-specific allometric equations to determine biomass and carbon stocks. A 2023 Landsat image was used to map mangrove distribution with the help of geographic information system (GIS)-based spatial analyses. Anthropogenic emissions were estimated based on available data for transport, livestock and poultry, liquefied petroleum gas (LPG) consumption, and electricity. The results showed that Gresik Subdistrict had the highest total emissions, at 6,795.91 t CO2-eq yr-1, and Ujungpangkah Subdistrict had the highest carbon stock value, at 264,803.16 t C. Spatial analysis showed that Kebomas, Panceng, and Gresik subdistricts needed additional mangrove areas of 52.07 ha, 50.21 ha, and 57.10 ha, respectively, to neutralize emissions under their current emission conditions. These results highlight the need for mangrove restoration as a crucial element of effective regional climate change mitigation and, thus, sustainable coastal management.
