Detecting declining forest health early is critical for timely intervention, yet traditional field sampling is too slow and large-scale genomics can be expensive. Remote sensing from aircraft or satellites gives wide coverage, but current methods often do not provide early or detailed biological information.
A new study by researchers at the University of Notre Dame, funded by NASA and published in Nature: Communications Earth & Environment, links leaf spectral reflectance with gene expression. The team measured reflectance on leaf surfaces and then analysed gene expression from the same samples. They worked on common tree species and recorded data at field sites.
The gene analysis targeted responses to water, drought, photosynthesis and plant pests or pathogens. For more than half of the genes analysed, the team found a strong correlation with specific reflectance wavelengths. Combining species maps from remote sensing with these reflectance–gene models could allow mapping of gene activity across whole forests, enabling faster management actions before tree health reaches a crisis.
Difficult words
- detect — to discover or notice something existsDetecting
- decline — to become worse or decrease in amountdeclining
- intervention — action to improve a situation or problem
- genomics — study of an organism's complete set of genes
- remote sensing — collecting information from aircraft or satellites
- reflectance — light energy that surfaces send back or reflect
- gene expression — process where a gene makes its product
- pathogen — an organism that causes disease in otherspathogens
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Discussion questions
- How might faster mapping of gene activity change decisions by people who manage forests?
- What are the advantages and disadvantages of using remote sensing instead of traditional field sampling?
- Would you support more funding for research that combines genomics and remote sensing? Why or why not?
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