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A non-invasive footprint technique for accurate identification of cryptic small mammal species : a sengi case study
Alibhai, Sk; Avenant, Nico; Oosthuizen, Maria Kathleen; Carlson, Lynn; Macfadyen, Duncan; Jewell, Zoe (Frontiers Media, 2026-01-27)
The acceleration of biodiversity loss highlights the need for practical, affordable species monitoring tools. A key requirement of monitoring is the accurate identification of species, a particular challenge with cryptic species. This study introduces a non-invasive footprint identification technology to classify two cryptic sengi species (Elephantulus myurus and Elephantulus intufi) - key bioindicators in the rapidly changing Southern African biomes. Front footprints were collected, using a custom Small Mammal Reference Track box, from live-captured individuals that were identified by experts in small mammal taxonomy and verified through genetic analyses. Morphometric features of the footprints (lengths, angles and areas) were extracted using JMP software. Linear Discriminant Analysis, based on nine key variables, achieved a mean classification accuracy of 94–96% across training, validation, and test datasets, robustly distinguishing the two species using a single footprint image. By integrating our field capture locations with data from the IUCN expert-defined ranges and the Global Biodiversity Information Facility, we demonstrate that FIT empowers non-experts to contribute reliable, high-resolution occurrence data. This scalable approach has the potential to transform community-science efforts, improving the accuracy of species distribution maps and ultimately strengthening conservation outcomes. Planned advancements include open-ended track tunnels and expanded machine learning models to monitor more small mammals in at-risk ecosystems. This approach offers a scalable, low-impact alternative to traditional trapping and genetic methods, reduces animal stress, morbidity and mortality, and empowers local communities to enhance data quality and monitoring through integration with traditional ecological knowledge.
A multivariate GARCH model with time-varying correlations : what do inflation data show in Ethiopia?
Likassa, Habte Tadesse; Chen, Ding-Geng (Din); Nadarajah, Saralees; Sema, Meskerem; Chen, Jenny K.; Temesgen, Shibru; Gotu, Butte (Springer, 2026)
Please read abstract in the article.
A multi-scale environmental niche model for the endangered dhole Cuon alpinus
Khatiwada, Monsoon Pokharel; Kunkel, Kyran E.; Wright, Wendy; Acharya, B.; Aung, Saw Soe; Bhumpakphan, Naris; Cheng, T.C.; Davis, C.; Ean, Tan Poai; Ferraz, Katia M.P.M.B.; Ghaskadbi, P.; Ghimirey, Y.P.; Gilbert, M.; Gupta, B.K.; Habib, B.; Haidir, I.; Havmoller, L.; Havmoller, R.W.; Jenks, K.E.; Kamler, J.F.; Khatiwada, A.P.; Li, S.; Macdonald, D.W.; Machmudah, F.; Mekiln, Y.; Namgyal, C.; Nawangsari, V.A.; Ngoprasert, D.; Nurvianto, S.; Rahman, H.A.; Rahman, S.C.; Rasphone, A.; Roux, P.; Seuaturien, N.; Shwe, N.M.; Songsasen, N.; Steinmetz, R.; Sukmasuang, R.; Thinley, P.; Tipkantha, W.; Traylor-Holzer, K.; Wahyudi, H.; Dalerum, Fredrik (Cambridge University Press, 2026)
The dhole Cuon alpinus is a large canid that is categorized as Endangered on the IUCN Red List and at risk of global extinction. Information on the spatial distribution of suitable habitat is important for conservation planning but is largely unavailable. We quantified the spatial distribution of potential range as well as the relative probability of dhole occurrence across large parts of the species’ global range. We used the MaxEnt algorithm to produce a multi-scale environmental niche model based on 24 environmental variables and dhole occurrence data from 12 countries. We identified three regions where dhole conservation should be focused: western India, central India, and across the Himalayan foothills through Southeast Asia. Connectivity between suitable areas was poor, so coordinated action among these regions should be a priority. For instance, transboundary dhole conservation initiatives across the Himalayas from southern China, Myanmar, north-east India, Nepal and Bhutan need to be initiated. We also highlight the value of improving dhole population viability on unprotected land and increasing monitoring in the northern parts of its historic distribution, in particular in areas within mainland China.
A conceptual participatory framework for integrating coding and robotics in early childhood education
Willemse, Kayla (Routledge, 2026)
Coding and robotics is an essential competency in the twenty-first century. In South Africa, coding and robotics is a mandatory subject in the Foundation Phase. However, successful integration into these early learning environments requires more than curricular inclusion, it also demands responsive support for educators navigating complex contextual realities. This study presents a framework, derived from a literature synthesis and participatory action research; to guide coding and robotics in early childhood education through playful learning using thematic data analysis. Co-constructed with ten Grade R educators and one external participant over a nine-month period in the Tshwane South district, data generation involved semi-structured interviews, observations, focus groups and a systematising expert interview. The framework, synthesised as NELO, comprises four interrelated components: Needs, External factors, the Learning process, and Outcomes. Findings indicate that educators require professional development, resources and collaboration initiatives to implement coding and robotics. The learning process of coding and robotics is progressive and embeds play-based, developmentally appropriate pedagogies while foregrounding localised and context-sensitive strategies. By bridging theoretical knowledge with practical realities, NELO offers a sustainable and scalable approach for the integration of coding and robotics in diverse early childhood education settings.
A critical review of the modelling and factors considered for permanent deformation of the unbound granular materials
Rugabandana, Gabriel; Boateng, Joseph Anochie; Maina, J.W. (James); Rimoy, Siya (Springer, 2026-02)
The elastoplastic behavior of Unbound Granular Materials (UGMs) under repeated loading plays a critical role in the performance and longevity of flexible pavements. This paper presents a comprehensive review of the permanent deformation modelling and factors considered in UGMs. The factors influencing resistance to permanent deformation such as stress magnitude, moisture content, gradation, density, porosity, particle morphology, mineralogical composition, are discussed, emphasizing their complex interdependence and impact on material behaviour. The study also examines the development and evolution of mathematical and empirical models used to predict permanent deformation under cyclic loading, highlighting that most existing models, primarily derived from repeated load triaxial (RLT) tests, remain empirical in nature, lack physical interpretation, and do not capture the true three-dimensional stress state experienced in the field. Rutting, the predominant distress mode in flexible pavements, arises from the accumulation of both elastic and plastic deformations across all pavement layers. Although numerous predictive models express accumulated strain as a function of load repetitions and deviator stress, they often neglect critical influences such as environmental conditions and shear strength of the subgrade. This review identifies limitations in current design practices and modeling approaches, provides insights into modern concepts in rutting analysis, and outlines future research needs for developing more mechanistic and physically meaningful models to predict the permanent deformation behavior of UGMs in pavements.