Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling δ(15)N from biochemical and structural leaf properties

Rapid quantification of biological nitrogen fixation using optical spectroscopy

Biological nitrogen fixation (BNF) provides a globally important input of nitrogen (N); its quantification is critical but technically challenging. Leaf reflectance spectroscopy offers a more rapid approach than traditional techniques to measure plant N concentration ([N]) and isotopes (δ15N). Here we present a novel method for rapidly and inexpensively quantifying BNF using optical spectroscopy. We measured plant [N], δ15N, and the amount of N derived from atmospheric fixation (Ndfa) following the standard traditional methodology using isotope ratio mass spectrometry (IRMS) from tissues grown under controlled conditions and taken from field experiments. Using the same tissues, we predicted the same three parameters using optical spectroscopy. By comparing the optical spectroscopy-derived results with traditional measurements (i.e. IRMS), the amount of Ndfa predicted by optical spectroscopy was highly comparable to IRMS-based quantification, with R2 being 0.90 (slope=0.90) and 0.94 (slope=1.02) (root mean square error for predicting legume δ15N was 0.38 and 0.43) for legumes grown in glasshouse and field, respectively. This novel application of optical spectroscopy facilitates BNF studies because it is rapid, scalable, low cost, and complementary to existing technologies. Moreover, the proposed method successfully captures the dynamic response of BNF to climate changes such as warming and drought.

Geographical origin traceability of mulberry leaves using stable hydrogen, oxygen, and carbon isotope ratios

Geographical discrimination of mulberry leaves is very important for their efficacy and quality as a traditional Chinese medicine. Stable hydrogen, oxygen, and carbon isotope ratios were measured in 292 mulberry leaves collected at 2 growth stages in 2 seasons from 8 regions of China. A stepwise linear discriminant analysis (LDA) approach were proposed to combine with stable isotope technology to tracing the origin of mulberry leaves. The results showed that leaves sampled in autumn were extremely depleted in 2H and 18O and slightly enriched in 13C compared with leaves sampled in summer, correlated with the effect of season, transpiration and photorespiration on stable isotopes. δ2H and δ18O of the leaves were enriched during the growth process. The overall discrimination accuracy of the autumn tender model was 81%, demonstrating that analysis of δ2H, δ18O, and δ13C is a promising technique for tracing the geographical origin of mulberry leaves, although season, growth stage and number of samples affect the accuracy of discrimination.

Unsupervised analysis of NIRS spectra to assess complex plant traits: leaf senescence as a use case

BACKGROUND

As a rapid and non-destructive method, Near Infrared Spectroscopy is classically proposed to assess plant traits in many scientific fields, to observe enlarged genotype panels and to document the temporal kinetic of some biological processes. Most often, supervised models are used. The signal is calibrated thanks to reference measurements, and dedicated models are generated to predict biological traits. An alternative unsupervised approach considers the whole spectra information in order to point out various matrix changes. Although more generic, and faster to implement, as it does not require a reference data set, this latter approach is rarely used to document biological processes, and does requires more information of the process.

METHODS

In our work, an unsupervised model was used to document the flag leaf senescence of durum wheat (Triticum turgidum durum). Leaf spectra changes were observed using Moving Window Principal Component Analysis (MWPCA). The dates related to earlier and later spectra changes were compared to two key points on the senescence time course: senescence onset (T0) and the end of the leaf span (T1) derived from a supervised strategy.

RESULTS

For almost all leaves and whatever the signal pre-treatments and window size considered, the MWPCA found significant spectral changes. The latter was highly correlated with T1 (0.59 ≤ r ≤ 0.86) whereas the correlations between the first significant spectrum changes and T0 were lower (0.09 ≤ r ≤ 0.56). These different relationships are discussed below since they define the potential as well as the limitations of MWPCA to model biological processes.

CONCLUSION

Overall, our study demonstrates that the information contained in the spectra can be used when applying an unsupervised method, here the MWPCA, to characterize a complex biological phenomenon such leaf senescence. It also means that using whole spectra may be relevant in agriculture and plant biology.

Using near-infrared reflectance spectroscopy (NIRS) to estimate carbon and nitrogen stable isotope composition in animal tissues

Stable isotopes analysis (SIA) of carbon and nitrogen provides valuable information about trophic interactions and animal feeding habits.We used near-infrared reflectance spectroscopy (NIRS) and support vector machines (SVM) to develop a model for screening isotopic ratios of carbon and nitrogen (δ 13C and δ 15N) in samples from living animals. We applied this method on dried blood samples from birds previously analyzed for δ 13C and δ 15N to test whether NIRS can be applied to accurately estimate isotopic ratios.Our results show a prediction accuracy of NIRS (R 2 > 0.65, RMSEP < 0.28) for both δ 13C and δ 15N, representing a 12% of the measurement range in this study.Our study suggests that NIRS can provide a time- and cost-efficient method to evaluate stable isotope ratios of carbon and nitrogen when substantial differences in δ 13C or δ 15N are expected, such as when discriminating among different trophic levels in diet.

Leaf development stages and ontogenetic changes in passionfruit (Passiflora edulis Sims.) are detected by narrowband spectral signal

During shoot development, leaves undergo various ontogenetic changes, including variation in size, shape, and geometry. Passiflora edulis (passionfruit) is a heteroblastic species, which means that it experiences conspicuous changes throughout development, enabling a morphological distinction between the juvenile and adult vegetative phases. Quantification of heteroblasty requires a practical, inexpensive, reliable, and non-destructive method, such as remote sensing. Moreover, relationships among ontogenetic changes and spectral signal at leaf level can be scaled up to support precision agriculture in passion fruit crops. In the present study, we used laboratory spectroscopic measurements (400-2500 nm) and narrowband vegetation indexes (or hyperspectral vegetation indexes - HVIs) to evaluate ontogenetic changes related to development and aging in P. edulis leaves. We also assessed leaf pigment concentration to further support the application of biochemical-related narrowband indexes. We report that 30-d-old leaves can be discriminated into developmental stages through their spectral signals. MSI (Moisture Stress Index) and NDVI₇₅₀ (Normalized Difference Vegetation Index ρ750) contribute most to the variation of age (15 to 30-d-old leaves) and developmental stage (phytomer positions along the plant axis) in passionfruit leaves. PRI (Photochemical Reflectance Index) played an important role in detecting age and development alterations, including heteroblasty. A biochemical and spectral comparison of pigments revealed that spectroscopy offered potential for diagnosing phenology in P. edulis, as some narrowband indexes correlated strongly with chlorophylls and carotenoids content. Narrowband vegetation indexes are found to be a suitable tool for monitoring passionfruit crops.

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing

Spatial heterogeneity of ecosystems crucially influences plant performance, while in return plant feedbacks on their environment may increase heterogeneous patterns. This is of particular relevance for exotic plant invaders that transform native ecosystems, yet, approaches integrating geospatial information of environmental heterogeneity and plant-plant interaction are lacking. Here, we combined remotely sensed information of site topography and vegetation cover with a functional tracer of the N cycle, δ15N. Based on the case study of the invasion of an N2-fixing acacia in a nutrient-poor dune ecosystem, we present the first model that can successfully predict (R 2 = 0.6) small-scale spatial variation of foliar δ15N in a non-fixing native species from observed geospatial data. Thereby, the generalized additive mixed model revealed modulating effects of heterogeneous environments on invader impacts. Hence, linking remote sensing techniques with tracers of biological processes will advance our understanding of the dynamics and functioning of spatially structured heterogeneous systems from small to large spatial scales.

Isoscapes resolve species-specific spatial patterns in plant-plant interactions in an invaded Mediterranean dune ecosystem

Environmental heterogeneity and plant-plant interactions are key factors shaping plant communities. However, the spatial dimension of plant-plant interactions has seldom been addressed in field studies. This is at least partially rooted in a lack of methods that can accurately resolve functional processes in a spatially explicit manner. Isoscapes, that is, spatially explicit representations of stable isotope data, provide a versatile means to trace functional changes on spatial scales, for example, related to N-cycling (foliar δ¹⁵N) and water use efficiency (WUE_i, foliar δ¹³C). In a case study in a nutrient-depleted Mediterranean dune ecosystem, we analysed the spatial impact of the invasive N₂-fixing Acacia longifolia on three native species of different functional types using δ¹⁵N and δ¹³C isoscapes and spatial autocorrelation analyses. Isoscapes revealed strong spatial patterns in δ¹⁵N and δ¹³C with pronounced species-specific differences, demonstrating distinct spatial ranges of plant-plant interactions. A coniferous tree and an ericaceous dwarf shrub showed significant enrichment in δ¹⁵N within a range of 5-8 m surrounding the canopy of A. longifolia, indicating input of N originating from symbiotic N₂-fixation by the invader. In the dwarf shrub, which was most responsive to invader influence, enrichment in δ¹³C additionally demonstrated spatially explicit changes to WUE_i, while a native N₂-fixer was unresponsive to the presence of the invader. Furthermore, δ¹⁵N and δ¹³C isoscapes yielded different patterns, indicating that plant-plant interactions can have distinct spatial distributions and ranges based on the process measured. Additionally, the magnitude of the effect differed between field situations with high and low invasion pressure. This study highlights that the spatial scale must be accounted for when assessing the effects and outcome of species interactions. Functional tracers such as stable isotopes enable us to quantify spatial ranges of plant-plant interactions, providing empirical data that can help to better understand and predict complex species interactions in multifaceted natural environments.