Naturally occurring compounds that can reduce methane production in anaerobic conditions have been studied for quite some time as feasible approaches to mitigate methane production in ruminant animals, especially those of commercial importance. Asparagopsis taxiformis (red algae) and Dictyota bartayresii (brown algae) are effective inhibitors of methane synthesis under in vitro anaerobic fermentation systems (Machado et al., 2014) likely because of their high concentration of secondary metabolites that are toxic to the typical rumen microbiota, including protozoa. In addition to phytoplankton (Palmer and Reason, 2009), Asparagopsis contains a high concentration of haloform compounds (e.g., bromoform, chloroform) while Dictyota has a high concentration of isoprenoid terpenes. Despite the economic and biological impact of diverse phytochemicals on reducing methane production in ruminant animals (Tedeschi et al., 2021), haloform compounds’ environmental impact and safety, in particular, are still unclear. In the present study, Munõz-Tamayo and collaborators (2021) listed relevant literature about the impact of A. taxiformis on ruminal methane production.

Concurrent to the understanding of mechanisms and biology behind the reduction of ruminal methane, mathematical models can lead the way to enhance the effectiveness of feeding A. taxiformis under commercial applications. Thus, in the present study, Munõz-Tamayo and collaborators (2021) sought to develop a mathematical model to understand the rumen fermentation changes in vitro experimentation containing extract of A. taxiformis by adapting a previously documented model by Muñoz-Tamayo et al. (2016).

Modeling development, calibration, and evaluation steps should be independent of each other, requiring complete, distinct, and separate databases (Tedeschi, 2006). However, in rare circumstances where such requirements cannot be met because data availability is scarce, the cross-validation technique, when possible, should be considered to assess data dispersion’s effects on model adequacy. In other situations, clear reasoning for failing to do so must be addressed in the paper. In the present paper, Munõz-Tamayo and collaborators (2021) explained the limitations in their modeling efforts were primarily due to the lack of ideal data: “experiments with simultaneous dynamic data of bromoform, volatile fatty acids, hydrogen, and methane.” Regardless of the availability of ideal data, improvements in the conceptual model are warranted to include amino acids and branched-chain fatty acids fermentation dynamics in the rumen and the fluctuations in ruminal pH.

References

Machado L, Magnusson M, Paul NA, Nys R de, Tomkins N (2014) Effects of Marine and Freshwater Macroalgae on In Vitro Total Gas and Methane Production. PLOS ONE, 9, e85289. https://doi.org/10.1371/journal.pone.0085289

Muñoz-Tamayo R, Chagas JC, Ramin M, Krizsan SJ (2021) Modelling the impact of the macroalgae Asparagopsis taxiformis on rumen microbial fermentation and methane production. bioRxiv, 2020.11.09.374330, ver. 4 peer-reviewed and recommended by PCI Animal Science. https://doi.org/10.1101/2020.11.09.374330

Muñoz-Tamayo R, Giger-Reverdin S, Sauvant D (2016) Mechanistic modelling of in vitro fermentation and methane production by rumen microbiota. Animal Feed Science and Technology, 220, 1–21. https://doi.org/10.1016/j.anifeedsci.2016.07.005

Palmer CJ, Reason CJ (2009) Relationships of surface bromoform concentrations with mixed layer depth and salinity in the tropical oceans. Global Biogeochemical Cycles, 23. https://doi.org/10.1029/2008GB003338

Tedeschi LO (2006) Assessment of the adequacy of mathematical models. Agricultural Systems, 89, 225–247. https://doi.org/10.1016/j.agsy.2005.11.004

Tedeschi LO, Muir JP, Naumann HD, Norris AB, Ramírez-Restrepo CA, Mertens-Talcott SU (2021) Nutritional Aspects of Ecologically Relevant Phytochemicals in Ruminant Production. Frontiers in Veterinary Science, 8. https://doi.org/10.3389/fvets.2021.628445

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. 

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

Farm animals differ in their ability to respond to the many environmental challenges they face. Such challenges include infectious diseases, metabolic diseases resulting from inadequate coverage of dietary needs, as well as the diverse consequences of climate change. Various concepts exist to characterise the responses of animals to different types of challenges. This article by Friggens et al. (2022) focuses on resilience, providing a conceptual definition and proposing a method to quantify resilience in dairy cows.

The first part of the paper provides a definition of resilience and highlights its differences and relations with the related concepts of robustness, and, to a lesser extent, resistance and tolerance. In essence, resilience is the ability of an animal to bounce back quickly after a challenge of limited duration. On the other hand, robustness is the ability of an animal to cope with conditions that are overall unfavourable. From these conceptual and intuitive definitions, there are several difficulties precluding the design of concrete methods to measure resilience. First, there is some degree of overlap between the concepts of resilience, robustness, resistance and tolerance. Secondly, resilience is a multidimensional concept whereby resilience to a given perturbation does not imply resilience to other types of perturbation, e.g. resilience to a challenge by a specific pathogen does not imply resilience to a nutritional challenge. A further difficulty in the measure of resilience is the fact that different animals may be exposed to challenges that are different in nature and in number. The authors argue that although resilience cannot be measured directly (it should be seen as a latent construct), it is possible to quantify it indirectly through its consequences.

In the second part of the paper, the authors propose a method to quantify resilience of individual dairy cows. The method is based on the premise that resilient animals should be kept longer in their herd than non-resilient animals. The main criterion in the evaluation is therefore the ability of cows to re-calve. Each cow that is calving receives a certain number of points, to  which, in each lactation, bonus points are added for higher milk production and penalty points are removed for each insemination after the first one, for each disease event and for each day of calving interval above some herd specific value. Therefore, cows have a resilience score in each lactation. They also have a lifetime resilience score obtained by summing the scores for all the lactations, that gets bigger as the cow has more calves, and that also takes the age at first calving into account. In a previous study, Adriaens et al. (2020) showed that higher resilience scores were associated with fewer drops in milk yield and more stable activity dynamics.

Starting from theoretical considerations on the notion of resilience, this paper describes a concrete method to quantify animal-level resilience on farm. Such quantification will be useful for breeding and culling decisions. Finally, the general framework to design resilience measures that is presented will be useful to researchers working on the quantification of farm animal resilience using new methods and data sources.

References

Adriaens I, Friggens NC, Ouweltjes W, Scott H, Aernouts B and Statham J 2020. Productive life span and resilience rank can be predicted from on-farm first-parity sensor time series but not using a common equation,  across farms. Journal of Dairy Science 103, 7155-7171.https://doi.org/10.3168/jds.2019-17826

Friggens, N.C. , Adriaens, I., Boré, R., Cozzi, G., Jurquet, J., Kamphuis, C., Leiber, F., Lora, I., Sakowski, T., Statham, J., De Haas, Y. (2022). Resilience: reference measures based on longer-term consequences are needed to unlock the potential of precision livestock farming technologies for quantifying this trait. Zenodo, 5215797, ver. 5 peer-reviewed and recommended by Peer community in Animal Science. https://dx.doi.org/10.5281/zenodo.5215797

As the world slowly (or not so slowly) warms, the ability to regulate heat becomes even more pertinent for livestock kept in enclosed areas. Trees are not always present on land grazed by sheep, and when the pasture has some forestation, the coverage will provide varying degrees of shade. In this study by Ginane et al. (2025), ewes kept in enclosures with different levels of tree cover were observed at different times over a period of three years to investigate the extent to which the animals chose to spend time in the shade. By using fields with very different provision of shade (approximately 1, 40, and 81% shade, respectively), the authors wanted to test the hypothesis that ewes would actively seek out tree shade when the combined temperature and humidity increased – especially if the conditions reached levels associated with heat stress. Even at the lowest provision of shade, which consisted of a single tree in the paddock, all ewes could fit within the shade cast by the tree; but if the distribution of ewes or groups of ewes were random, i.e. independent of shade, the likelihood of these ewes being in the shade by chance was effectively 1%. By factoring in the element of chance, the authors found that mean shade use was greater than the tree canopy cover for the low and medium shade treatments, whereas it didn’t differ from chance for the densely forested treatment. Across treatments, all ewes spent just under 60% of the observation time grazing, and the ewes with the low and medium level of shade actively selected shade for foraging activity, whereas the ewes with over 80% canopy cover avoided it. Across treatments, shade was used primarily for resting and ruminating.

Tree cover affected the availability of forage in a negative manner, with more biomass available for ewes in the low shade treatment and significantly less in the high treatment, although this did not translate into significant differences in live weight or body condition score. Using this information, Ginane et al. (2025) calculated the optimal level of tree cover to be somewhere between the low and medium cover, at roughly 30 trees per hectare – preferably spread out over the area to offer different locations of shade and to encourage a natural spread of manure.

This longitudinal study of shade use by ewes provides novel and useful information on the positive and negative effects of tree cover in paddocks used to rear ewes with lambs. The authors raise the limitation of the study themselves, and they would have liked to also include observations on non-sunny days, to be able to eliminate place preferences independently of shade availability. But the clever calculation of active shade-selection makes this study easily applicable for use in the assessment of paddock suitability for pregnant ewes.

References

Cécile Ginane, Mickaël Bernard, Véronique Deiss, Donato Andueza, Camille Béral (2025) Shade use, welfare and performance of ewes grazing in temperate silvopastures differing in tree density. Zenodo, ver.4 peer-reviewed and recommended by PCI Animal Science https://doi.org/10.5281/zenodo.15001481