This study explores the dynamics of developing an agropastoral cattle production system based on natural permanent grasslands in southern France, using the Fin Gras du Mézenc PDO as a case study. To comprehend interactions between the multifunctionality of grazing systems and production quality, we propose the concept of extended quality, which combines intrinsic and extrinsic dimensions, integrating material aspects, social construction, and territorial inscription. We ask whether the shaping of extended quality can facilitate the structuring and maintenance of the functional integrity of a suckler farming system over time. To account for both the technical and territorial dimensions of quality, our analysis focuses on an agroecosystem embedded in and interacting with a broader socio-technical and market environment. The article is based on an interdisciplinary qualitative methodology, situated at the intersection of biotechnical analysis of livestock systems (farm trajectories) and socio-historical methodology (interviews, archives). Our results show a grassland-pastoral system structured around socio-technical know-how in cattle fattening. From the 1970s, this system was challenged by dairy expansion and lean cattle, before quality-meat specifications in the 1990s reconfigured socio-technical networks, generating enduring economic and social value for the stakeholders of the agroecosystem. In conclusion, extended quality appears to be a fruitful approach to the reconstruction of a livestock grazing agroecosystem’s functional integrity, achieved by the gradual reorganisation of its various functions over time. The diachronic perspective developed here highlights the crucial importance of the elaboration and commercialization and cognitive renewal functions, which are critical dimensions that exert long-term influence on other functional dimensions.
Pasture condition assessments assist pastoralists, regulators, and policy makers in making informed decisions around livestock production and the preservation of natural resources in the Kimberley rangelands of Western Australia (WA). Reliable qualitative assessments of pasture condition require assessors with extensive expertise, which means frequent and reproducible assessments can be difficult to achieve. To develop a quantitative approach that can complement existing qualitative assessment approaches in the Kimberley, we investigated the use of simple classification tree models to predict pasture condition using assessment data from the Western Australian Rangeland Monitoring System (WARMS). Quantitative traits were derived from WARMS observation data for three major pasture groups in the Kimberley region and assessed for variable importance using random forest models. The traits with highest variable importance were used to train classification tree models for each pasture group. Important variables identified from random forests and classification trees were the percentage of quadrats containing at least one of a set of desirable perennial species and the percentage of quadrats without perennials. Classification trees selected to represent each pasture group had prediction accuracies between 0.71 and 0.81 when applied on reserved WARMS testing data, and between 0.65 and 0.74 when applied on independently collected validation data, indicating they generally performed well when used on data from the Kimberley rangelands. The classification tree models generated here can be used to complement qualitative assessments of pasture condition and to provide paddock-scale assessments, helping to inform decision making in the management of important WA pastoral resources.
Rangelands cover approximately 80% of Australia's land surface and encompass savannas, woodlands, shrublands, and grasslands. Their sparse canopy cover, spatial heterogeneity, and high rainfall variability make aboveground biomass (AGB) difficult to measure, model and monitor, posing challenges for robust carbon accounting. Satellite remote sensing is essential for monitoring biomass over such vast and remote areas but cannot directly measure AGB and requires reliable calibration data. Here we assess the utility of uncrewed aerial vehicle laser scanning (ULS) for plot-scale assessment of AGB, as a key step toward scaling biomass estimates using satellite imagery. We used field-based estimates of AGB collected in 77 plots from 11 properties to test relationships with ULS derived structural metrics. Multiple combinations of woody canopy height and cover metrics were evaluated using Ordinary Least Squares (OLS) regression. A model based on a single ULS derived metric, percentage woody canopy cover taller than 3.5 m (pct_gt3p5m), could linearly account for 78% of the variability in AGB, with a Mean Absolute Error (MAE) of 7.19 Mg ha-1 and minimal bias (-0.10%). The moderate RMSE and unbiased nature of this relationship across diverse rangelands is encouraging for regional and continental scale mapping of AGB with airborne LiDAR systems. Predictions based on the same single metric had less uncertainty at individual property scales when local models were fitted. ULS is a practical pathway for wall-to-wall modelling of AGB estimates at 10-1000 ha scales and can bridge field measurements with satellite-based models, improving the rigour and transparency in carbon accounting in rangelands.
Woody plant biomass in savanna landscapes exhibits considerable variability; however, biomass variation in African multi-use savannas remains poorly understood. Thus, the study evaluated how areas dominated by encroaching bush species, Senegalia mellifera, Dichrostachys cinerea, and Terminalia sericea, varied in terms of wood quantity, tree equivalence and tree-based evapotranspiration equivalence. The study used a factorial design with two factors (field site and farm), with each farm comprising three field sites, and each field site was dominated by a different encroacher bush species. The Bush Biomass Quantification Tool was used to derive quantitative parameters for the field sites. The study results showed no difference (P > 0.05) in the tree equivalence of sites dominated by different encroacher bush species. However, the Evapotranspiration Tree Equivalence (ETTE) was higher (P < 0.05) in sites dominated by S. mellifera (59,000 ETTE ha–1) compared to those dominated by D. cinerea (17,965 ETTE ha–1) and T. sericea (14,894 ETTE ha–1). Wood quantity was greater (P < 0.05) in sites dominated by S. mellifera (10,095 kg DM ha–1) compared to sites dominated by D. cinerea (6487 kg DM ha–1) and T. sericea (2440 kg DM ha–1). The study concluded that different quantities of wood and bush-feed suitable biomass can be harvested from sites dominated by different encroacher bush species.
The early IPCC assessment reports (2001, 2007) predominantly conceptualised livestock in technical and efficiency-oriented terms, focusing on productivity and technological innovations, while the 2014 and 2022 reports embed livestock within broader socio-environmental frameworks, explicitly linking it to diet and health, ecosystem services, and social justice. This discursive evolution illustrates a paradigmatic shift from sectoral mitigation to holistic sustainability paradigms. Nonetheless, the heterogeneity of livestock systems and context calls for more cross-cutting, context-sensitive metrics to inform equitable and evidence-based climate policy.
