New Imaging Method Offers Breakthrough in Forest Soil and Tree Analysis

A recent study examined how near-infrared (NIR) spectroscopy can effectively be used to monitor forest ecosystems. Published in Geoderma Regional, this study was led by J. A. Arias-Rios from the Instituto de Investigaciones Forestales y Agropecuarias Bariloche (IFAB) (1). The findings of this study help to demonstrate how NIR spectroscopy, as a rapid, efficient, and non-destructive technique, can provide insights into soil health and tree composition. As a result, this study can potentially help improve the conservation of forests and ensure sustainable forest management (1).

Forest ecosystems are currently dealing with the ongoing impacts of climate variation and anthropogenic pressures. Climate variation, which is understood as the long-term shift in weather patterns, is influencing the continued development of forests and the environment more generally (2). Meanwhile, anthropogenic activities, especially as they relate to economic activity, have resulted in the steady decrease of forested land and leading to biodiversity loss. Forests cover approximately one-third of all land on Earth, and they are essential to human health (3).

Beautiful green mossy forest in sweden | Image Credit: © Jens - stock.adobe.com

As a result, scientists are investigating and observing these changes to encourage environmental sustainability. Traditionally, assessing the ecological health of a forest requires expensive equipment and a significant amount of time. In their study, the researchers attempted to show that by applying NIR spectroscopy, they could classify, predict, and analyze both soil and leaf samples with improved accuracy (1).

As part of their experimental procedure, the researchers collected soil samples from four depths across three different land-use types: native forests, grazed grasslands, and horticultural lands (1). They also gathered leaf samples from two provenances of Nothofagus alpina, a tree species native to the southern Andes. These samples were analyzed using NIR spectroscopy, which works by measuring the reflectance of NIR light to capture information on chemical and biological composition (1).

Using principal component analysis (PCA), the team was able to clearly differentiate soil samples by both land use and depth. This information allowed them to distinguish leaf samples according to their provenance (1). This ability to discriminate between sample origins highlights the method's potential for ecological classification and monitoring.

More importantly, the NIR spectroscopy-based models achieved high predictive accuracy for several soil traits central to ecosystem function. The models performed particularly well in estimating microbial biomass (R² = 0.80), biological activity (R² = 0.94), and total carbon content (R² = 0.86) (1). These traits are critical indicators of soil health and are directly tied to nutrient cycling and carbon sequestration.

Although the results for soil analyses were encouraging, the models were less reliable when it came to leaf pigment estimation, with R² values ranging between 0.60 and 0.40 (1). This indicates that although NIR spectroscopy holds promise for plant characterization, especially for large-scale applications, additional refinement of the method is needed to improve its accuracy for assessing leaf traits (1).

Another aspect of this study worth noting is that the authors compared relatedness matrices derived from NIRS data with those generated from genetic analysis. The low correlations between these data sets suggest that both approaches provide unique and complementary information (1). This finding reinforces the value of integrating NIR spectroscopy with traditional genetic and ecological tools for a more comprehensive understanding of ecosystem dynamics (1).

With deforestation and land degradation continuing to threaten ecosystems worldwide, NIR spectroscopy could provide governments, researchers, and conservationists with a powerful new tool for tracking forest health.

The study’s authors emphasize the need for further methodological improvements for tree leaf analysis (1). However, the main conclusion the authors want people to draw from their study is that NIR spectroscopy has a clear role to play in forest conservation (1). By offering a non-destructive, rapid, and scalable alternative to traditional methods, NIR spectroscopy serves as an improved method that can potentially help change how we monitor and manage the world’s forest ecosystems.

References

1. Alvarez, V. E.; Arias-Rios, J. A.; Guidalevich, V.; et al. Using Near-infrared Spectroscopy as a Cost-effective Method to Characterise Soil and Leaf Properties in Native Forest. Geoderma Reg. 2025, 40, e00948. DOI: 10.1016/j.geodrs.2025.e00948
2. United Nations, What Is Climate Change? UN.org. Available at: https://www.un.org/en/climatechange/what-is-climate-change (accessed 2025-05-01).
3. World Wildlife Fund, Deforestation and Forest Degradation. World Wildlife Fund. Available at: https://www.worldwildlife.org/threats/deforestation-and-forest-degradation (accessed 2025-05-01).