Livestock grazing is one of the most widespread human pressures on grasslands worldwide. Its effects can vary: while moderate grazing may support biodiversity in some systems, heavier grazing is often associated with declines in productivity and shifts in species composition. Monitoring these changes is challenging because they involve not only vegetation cover, but also plant functional traits and the way species interact within communities.
In a study published on February 3, 2026, in Journal of Remote Sensing (DOI: 10.34133/remotesensing.0732), researchers from Peking University, Beijing Forestry University, Inner Mongolia University, the University of Twente, and Sun Yat-sen University investigated whether drone-based hyperspectral data could be used to monitor these ecological changes in the Xilin Gol Grassland Nature Reserve in Inner Mongolia, China.
The researchers found that drone observations could be used to estimate aboveground biomass and several plant functional traits with useful accuracy. Across the grazing gradient, biomass generally declined as grazing intensity increased, particularly under heavy grazing. At the same time, several nutrient-related traits tended to decrease, while traits such as leaf thickness and leaf carbon content tended to increase, consistent with a shift toward more stress-tolerant plant strategies.
The study also showed that, under heavier grazing, relationships between plant traits and biomass became stronger. In addition, functional diversity was more positively associated with biomass at higher grazing intensity. Patterns in trait networks were also linked to biomass, with less connected trait relationships associated with lower biomass under stronger grazing pressure. Together, these results suggest that changes in plant traits and community organization may provide additional insights into grassland responses to grazing.
“This study shows that monitoring grasslands may benefit from looking beyond how much vegetation is present, to also understanding how plant traits and community structure change under grazing pressure.” said Dr. Yiwei Zhang from Peking University, the study’s first author.
The work was based on a long-term grazing experiment established in 2013, including grazing exclusion, light grazing, moderate grazing, and heavy grazing treatments. By combining drone observations with field measurements, the researchers were able to relate patterns observed from the air to ecological changes on the ground.
The broader implication of this study is that monitoring grasslands may benefit from moving beyond simple measures of vegetation quantity. By capturing changes in plant traits and community organization, remote sensing approaches such as this may provide complementary information on how ecosystems respond to grazing pressure. This could support more comprehensive and timely assessment of grassland condition, particularly in regions where large-scale field monitoring is difficult.
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References
DOI
10.34133/remotesensing.0732
Original Source URL
https://spj.science.org/doi/10.34133/remotesensing.0732
About Journal of Remote Sensing
The Journal of Remote Sensing is an online-only Open Access Science Partner Journal published in affiliation with Aerospace Information Research Institute, Chinese Academy of Sciences (AIR-CAS) and distributed by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Journal of Remote Sensing is editorially independent from the Science family of journals and AIR-CAS is responsible for all content published in the journal. To learn more about the Science Partner Journal program, visit the SPJ program homepage.