Natural grasslands are being progressively degraded around the world due to human-induced action (e.g., overgrazing), but there is neither a widely accepted conceptual framework to approach degradation studies nor a clear definition of what “grassland degradation” is. Most of the drivers, processes, and consequences related to grassland degradation are widespread and are usually separately quoted in the literature. In this paper, we propose a comprehensive framework with different conceptual categories, for monitoring grassland degradation, and a new definition based on current ones. We provide a conceptual update of grassland degradation based on a literature review and an expert survey, focused on the Río de la Plata grasslands (RPG). We identified “drivers” as external forces or changes that cause degradation; “processes” as measurable changes in grasslands conditions that can be evaluated using indicators; and “consequences” as the impacts or results of the process of grassland degradation. We expect that this conceptual framework will contribute to monitoring programs, to support management decisions, to design conservation measures, and to communicate the importance of grasslands conservation and the different concepts involved. Particularly for RPG, we expect that this paper will contribute to promote sustainable management practices in this important and often neglected ecosystem.
Digital agriculture (DA) can contribute solutions to meet an increase in healthy, nutritious, and affordable food demands in an efficient and sustainable way. South America (SA) is one of the main grain and protein producers in the world but the status of DA in the region is unknown. A systematic review and case studies from Brazil, Argentina, Uruguay, and Chile were conducted to address the following objectives: (1) quantify adoption of existing DA technologies, (2) identify limitations for DA adoption; and (3) summarise existing metrics to benchmark DA benefits. Level of DA adoption was led by Brazil and Argentina followed by Uruguay and at a slower rate, Chile. GPS guidance systems, mapping tools, mobile apps and remote sensing were the most adopted DA technologies in SA. The most reported limitations to adoption were technology cost, lack of training, limited number of companies providing services, and unclear benefits from DA. Across the case studies, there was no clear definition of DA. To mitigate some of these limitations, our findings suggest the need for a DA educational curriculum that can fulfill the demand for job skills such as data processing, analysis and interpretation. Regional efforts are needed to standardise these metrics. This will allow stakeholders to design targeted initiatives to promote DA towards sustainability of food production in the region.
In countries where livestock production based on native grasslands is an important economic activity, information on structural characteristics of forage is essential to support national policies and decisions at the farm level. Remote sensing is a good option for quantifying large areas in a relative short time, with low cost and with the possibility of analyzing annual evolution. This work aims at contributing to improve grazing management, by evaluating the ability of remote sensing information to estimate forage height, as an estimator of available biomass. Field data (forage height) of 20 commercial paddocks under grazing conditions (322 samples), and their relation to MODIS data (FPAR, LAI, MIR, NIR, Red, NDVI and EVI) were analyzed. Correlations between remote sensing information and field measurements were low, probably due to the extremely large variability found within each paddock for field observations (CV: Around 75%) and much lower when considering satellite information (MODIS: CV: 4%–6% and Landsat:CV: 12%). Despite this, the red band showed some potential (with significant correlation coefficient values in 41% of the paddocks) and justifies further exploration. Additional work is needed to find a remote sensing method that can be used to monitor grasslands height.
9 August 2023 in Remote Sensing Applications: Society and Environment
Most countries lack effective policies to manage climate risks, despite growing concerns with climate change. The authors analyzed the policy evolution from a disaster management to a risk management approach, using as a case study four agricultural droughts that impacted Uruguay’s livestock sector in the last three decades. A transdisciplinary team of researchers, extension workers, and policy makers agreed on a common conceptual framework for the interpretation of past droughts and policies. The evidence presented shows that the set of actions implemented at different levels when facing droughts were mainly reactive in the past but later evolved to a more integral risk management approach. A greater interinstitutional integration and a decreasing gap between science and policy were identified during the period of study. Social and political learning enabled a vision of proactive management and promoted effective adaptive measures. While the government of Uruguay explicitly incorporated the issue of adaptation to climate change into its agenda, research institutions also fostered the creation of interdisciplinary study groups on this topic, resulting in new stages of learning. The recent changes in public policies, institutional governance, and academic research have contributed to enhance the adaptive capacity of the agricultural sector to climate variability, and in particular to drought. This study confirms the relevance of and need to work within a transdisciplinary framework to effectively address the different social learning dimensions, particularly those concerning the adaptation to global change.