The predominant form of agriculture in sub-Saharan Africa is mixed crop and livestock production, typically in extensive systems characterised by low productivity and little input (Tui et al., 2021). Such extensive systems experience many challenges, including access to rangeland and other sources of livestock feed, loss of soil quality, increasingly unpredictable climate but also operational constraints such as access to markets and veterinary care.

The work by Gobvu and collaborators (2025) addresses livestock farming sustainability specifically in the context of a Transfrontier Conservation Area (TFCA). A TFCA is defined as part of an ecological region reaching across boundaries of two or more countries and in which there are protected areas as well as resource use areas. TFCAs are founded to facilitate collective management of resources for the benefit of biodiversity as well as socio-economic development (SADC, 2025).

Livestock farming in TFCAs face additional challenges arising from the tension between biodiversity protection and resource use, such as wildlife predation on livestock, competition between livestock and wildlife for feed and water as well as spread of infections between livestock and wild animals (Matseketsa et al., 2019; Caron et al., 2013; Cumming, 2011).

The paper reports a study that was part of a larger project (EU-ProSuLi project, Caron et al.,  2022) aiming at promoting local development and well-being of residents in the Great Limpopo TFCA, with focus on the Sengwe Communal Area in Zimbabwe. The specific aim was to test a methodology for identifying interventions that are aligned with the needs of the local stakeholders (demand-driven interventions. Anticipatory scenario building in the context of workshops was used in combination with individual questionnaires.

Community representatives (n=31) were purposefully selected for their expected ability to act as knowledge brokers. A team of 10 facilitators supported the discussion through plenary and group work sessions. The participants were asked to identify factors of change with impact on local community livelihood, and subsequently to vote to select the most influential factors. Different future states for the year 2038, resulting from the impact of the factors of change, were discussed. In a follow-up workshop, participants were asked to propose activities that would support the development towards the most desirable scenario. In addition, a questionnaire was distributed through semi-structured/structured interviews to 126 households in nine villages.

Results were largely similar and complementary between the two approaches. Preferred interventions were: restocking herds with locally adapted breeds, training in livestock management, marketing support, feed development and value addition, loan schemes for investment in livestock production and support for animal health interventions to reduce the heavy disease burden. Whereas the participatory process is time consuming and requires considerable human resources, it is important to ensure locally relevant interventions are chosen, and it is in itself part of the process towards successful implementation of these interventions.

The study is thoughtfully designed based on previous work by the authors. The paper is well written and has been further improved through the reviewer feedback and revision process.

References

Caron, A., Miguel, E., Gomo, C., Makaya, P., Pfukenyi, D.M., Foggin, C., Hove, T. and de Garine-Wichatitsky, M., 2013. Relationship between burden of infection in ungulate populations and wildlife/livestock interfaces. Epidemiology & Infection, 141 (7), pp.1522-1535. https://doi.org/10.1017/S0950268813000204

Caron, A., Mugabe, P., Bourgeois, R., Delay, E., Bitu, F., Ducrot, R., Fafetine, J., Fynn, R., Guerbois, C., Motsholapheko, M. and Daré, W., 2022. Social-ecological System Health in  Transfrontier Conservation Areas to Promote the Coexistence Between People and Nature. One Health Cases. https://doi.org/10.1079/onehealthcases.2022.0005 

Cumming, D. H. M. 2011. Constraints to conservation and development success at the wildlife-livestock-human interface in southern African transfrontier conservation areas: a preliminary review. Wildlife Conservation Society, New York.  http://www.wcs-ahead.org/workinggrps_kaza.html

Gobvu, V. Ncube, S. Imbayarwo-Chikosi, V.E., Bourgeois, R. Mugabe, P.H. and Caron A. 2025. Preferred livestock interventions for small-scale farmers in the Great Limpopo Transfrontier Conservation Area: a demand-driven and participatory approach. HAL, ver.5 peer-reviewed and recommended by PCI Animal Science. https://hal.science/hal-04060712

Matseketsa, G., Muboko, N., Gandiwa, E., Kombora, D.M. and Chibememe, G., 2019. An assessment of human-wildlife conflicts in local communities bordering the western part of Save Valley Conservancy, Zimbabwe. Global Ecology and Conservation, 20, p.e00737. https://doi.org/10.1016/j.gecco.2019.e00737 

Tui, S.H.K., Descheemaeker, K., Valdivia, R.O., Masikati, P., Sisito, G., Moyo, E.N., Crespo, O., Ruane, A.C. and Rosenzweig, C., 2021. Climate change impacts and adaptation for dryland farming systems in Zimbabwe: a stakeholder-driven integrated multi-model assessment. Climatic Change, 168 (1-2), p.10. https://doi.org/10.1007/s10584-021-03151-8 

South African Development Community. 2025. Transfrontier Conservation Areas.  . Consulted 7 January 2025. https://www.sadc.int/pillars/transfrontier-conservation-areas

With the increasing use of cage-free housing systems for laying hens comes the challenge of monitoring the behaviour of individual hens in large enclosures where they can be not only on the floors but on different levels. The aim of the present study by Gebhardt-Henrich et al., (2023) was to validate a Radio Frequency Identification (RFID) system with the capacity to track a large number of hens for different research and applied purposes where behaviour monitoring is relevant, such as heritability estimates for breeding programs.

In a housing system with 225 birds per pens, 26 antennae were placed at different locations. All birds in 5 pens were equipped with a glass tag in a custom-developed leg band. For validation purposes, the behaviour of three hens who could move between two pens was also monitored on video. Equipping these hens with colour-coded backpacks made them identifiable on video.

Matching the antennae detection of the focal birds with the behaviour observation showed that the antennae were able to detect a hen on the right tier in > 90% of cases, but that match on antenna level was lower.

The limitations of the system are also discussed in this concise methods paper that will be helpful to many researchers interested in tracking laying hens in loose housing systems.

Gebhardt-Henrich, S.G., Kashev, A., Petelle, M.B., Toscano, M.J., 2023. Validation of a Radio frequency identification system for tracking location of laying hens in a quasi-commercial aviary system. bioRxiv 2023.02.16.528820. ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.02.16.528820

In production animals, behavioural activity plays a crucial role across a wide range of scientific disciplines and is often measured for various purposes depending on the field: ethology, animal welfare, reproduction, animal production, and so on. Historically, direct observation was the primary method of collecting such data, a process that was time-consuming and prone to possible observer bias. With the advent of automated systems and sensors, behavioural activity can now be recorded continuously and non-invasively, leading to a growing body of more reliable data  (1). However, the lack of standardisation in how these data are calculated and interpreted has created challenges for cross-study comparisons. To fully harness the potential of studying behavioural activity, scientific studies must harmonise the methods used to calculate this measure. Standardising these methods would make it easier to compare results and identify possible gaps in knowledge.

In the work by van Dixhoorn et al.(2), the authors examine the various metrics most commonly used to study behavioural activity. Through a series of examples, they address the definitions, calculation methods, and biological significance of metrics such as overall activity, fluctuations around mean activity, cyclicity of activity, and synchrony between animals. The authors suggest how these different metrics can be applied in specific contexts and guide readers in using appropriate terminology to ensure future studies are more easily comparable. In addition, by clarifying these concepts, the authors provide researchers with the tools to make informed decisions about which metric best suits their study's objectives.

A key contribution of this work is its emphasis on standardising the metrics and terminology used in behavioural activity studies. Studies using different metrics may arrive at conclusions that appear contradictory, not because of actual differences in animal behaviour, but due to inconsistencies in how behaviour is quantified. By advocating for a common framework, the authors aim to improve the replicability of studies, facilitate meta-analyses, and allow for a more cohesive understanding of animal behaviour across different research groups. This, in turn, could accelerate the identification of key behavioural indicators, ultimately leading to better animal management practices and welfare assessments.

This article provides a timely and valuable contribution to the field of animal science. As technology continues to evolve, so too must our methods for interpreting the vast amounts of data it generates (3). By ensuring that studies are comparable and data is interpreted consistently, the research community can work towards more meaningful discoveries in animal behaviour. I highly recommend this paper to researchers looking to deepen their understanding of activity metrics in animal behaviour studies.

References

1. Rushen J, Chapinal N, de Passilé AM (2012). Automated monitoring of behavioural-based animal welfare indicators. Animal Welfare 21(3):339-50. https://doi.org/10.7120/09627286.21.3.339 

2. van Dixhoorn IDE, Aubé L, van Zyl C, de Mol R, van der Werf J, Lardy R, Mialon MM, van Reenen CG, and Veissier I (2024). From data on gross activity to the characterization of animal behaviour: which metrics for which purposes?. Zenodo, 10420600, ver.5 peer-reviewed and recommended by PCI Animal Science. https://doi.org/10.5281/zenodo.10420600 

3. Riaboff L, Shalloo L, Smeaton AF, Couvreur S, Madouasse A, Keane MT (2022). Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data. Computers and Electronics in Agriculture 192:106610. https://doi.org/10.1016/j.compag.2021.106610 
 

To limit the use of antibiotics in the few days after hatching, it is necessary to improve the robustness of chicks during the early post-hatch period. This can be achieved by ensuring immediate access to feeds, optimizing the implantation and maturation of the microbiota and immune system of each chick, and minimizing exposure of stressors such as transportation. The study conducted by Guilloteau and colleagues (2024) compared the performance and health of chicks raised in conventional hatching systems with those raised in on-farm hatching systems. The authors showed that both systems yielded similar hatching percentage of eggs. Chicks from on-farm hatching systems exhibited higher body weights during the post-hatch period compared to those from conventional hatching, whereas health parameters were not affected by the system. An originality of the study was the examination of the benefits of the presence of an adult hen in hatching systems. The effects on chick traits were interpreted in relation to the hen behavior at hatching and a classification according to maternal or agonistic activities towards the chicks. However, the experimental design did not allow to make statistical correlations between hen behavior pattern and chick traits. Importantly, the presence of a hen decreased the hatching percentage, and this was likely associated with hen aggressiveness in the pen. The presence of the hen deteriorated the quality scores of the chicks in the on-farm hatching system, and increased mortality of chicks at hatching, negatively impacting chick weight gain and feed efficiency during the few days after hatching in both conventional and on-farm hatching systems. Thereafter, the effect of the presence of a hen on chick body weight was different according to the sex of the chicks and the type of hatching system. The presence of a hen did not reduce the parasitic load of the chicks nor improved clinical signs. No specific characterization of the fecal microbiota of the chicks was conducted, preventing the testing whether or not the presence of the hen affected the early implantation and maturation of the chick microbiome. Altogether, the data indicate that on-farm hatching systems are at least equivalent (in terms of health traits, feed efficiency) or even favorable (for faster growth in the early period after hatching) for chicks. Training the hens (considered as foster adults) to the presence of eggs and chicks or selecting hens according to specific activity behavioral patterns could be ways to establish better interactions between hens and chicks. Although the number and type of environmental stressors tested in the experiment differ from those in commercial farms, the article opens new perspectives for alternative hatching and farming practices.

Reference

Guilloteau LA, Bertin A, Crochet S, Bagnard C, Hondelatte A, Ravon L, Schouler C, Germain K, Collin A (2024) On-farm hatching and contact with adult hen post hatch induce sex-dependent effects on performance, health and robustness in broiler chickens. bioRxiv, 2023.05.17.541117. ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.05.17.541117.