Where, when, and why do plant volatiles mediate ecological signaling? The answer is blowing in the wind

Plant volatiles comprise thousands of molecules from multiple metabolic pathways, distinguished by sufficient vapor pressure to evaporate into the headspace under normal environmental conditions. Many are implicated as ecological signals, but what is the evidence—and how do they work? Volatiles diffuse, are carried by wind, and may be taken up by other organisms or degrade with exposure to atmospheric ozone, radicals, and UV light; visual signals such as color are not subject to these complications (but require a line of sight). Distantly related plants—and nonplants—produce many of the same volatiles, yet specific compounds and blends may be distinct. Here, I present a quantitative review of the literature on plant volatiles as ecological signals, illustrating a field that has focused on developing ideas as much as reporting primary data. I discuss advantages and constraints, review recent advances, and propose considerations for primary studies to elucidate particular functions of plant volatiles

Discerning Oriental from European beech by leaf spectroscopy: Operational and physiological implications

European beech (Fagus sylvatica L.) forests have recently experienced severe diebacks that are expected to increase in future. Oriental beech (Fagus sylvatica spp. orientalis (Lipsky) Greut. & Burd) is a potential candidate for assisted migration (AM) in European forests due to its greater genetic diversity and potentially higher drought resistance. Yet AM entails not only benefits, but also risks, and it is therefore important to monitor the progression of introduced (sub)species. Here, we demonstrate the potential of leaf spectroscopy to replace resourceintensive genetic analysis and field phenotyping for the discrimination and characterization of these two beech subspecies. We studied two European beech forests, one in France and one in Switzerland, where Oriental beech from the Greater Caucasus was introduced over 100 years ago. During two summers (2021, 2022), we measured leaf spectral reflectance, leaf morphological and biochemical traits from genotyped adult trees. Subspecies prediction models were developed separately for top-of-canopy leaves (amenable to remote sensing) and bottom-of-canopy leaves (easier to harvest) using partial least squares discriminant analysis (PLS-DA) and different sets of spectral predictors. Morphological, biochemical and spectra-derived leaf traits indicated that Oriental beech trees at the sites studied were characterized by higher lignin and nitrogen per unit leaf area than European beech, suggesting more protein-rich leaves on a per-area basis. The model based on top-of-canopy leaf reflectance spectra in the short-wave-infrared region (SWIR I: 1450–1750 nm) most accurately distinguished Oriental from European beech (BA = 0.86 ± 0.08, k = 0.72 ± 0.15), closely followed by models based on SWIR II, and on spectra-derived traits (BA ≥ 0.84, k ≥ 0.67). This study provides a proof-of-principle for the development of spectroscopy-based approaches when monitoring introduced species, subspecies or provenances. Our findings hold promise for upscaling to large forest areas using airborne remote sensing

Ecological chemistry of pest control in push-pull intercropping systems: What we know, and where to go?

Push-pull technology (PPT) employs mixed cropping for sustainable intensification: an intercrop repels or suppresses pests of the focal crop (push), while a trap crop attracts pests out of the field (pull), where they may be targeted for control. Underlying chemical-ecological mechanisms have been demonstrated in controlled settings, primarily for some of the best-established cereal PPT systems developed in east Africa. Yet, many questions remain regarding mechanisms, and strategies to adapt PPT for different crops and locations. We conducted a systematic review of scientific literature on PPT and related practices for biological control of pests of food and fodder. Of 3335 results, we identified 45 reporting on chemistry of trap- or intercropping systems for pest control, of which 30 focused on cereals or African pests. Seven of these reported primary chemical data: measurements from glasshouse and laboratory studies (5), or of field-collected samples (2). From these 30, we provide a database of compounds, discussing degrees of evidence for their mediation of push-pull. We depict hypothesized spatial distributions of selected compounds in PPT fields from physical properties and emission/exudation rates, and design of the east African cereal PPT system, and discuss influences on activity in field settings likely to affect success

Ecological Chemistry of Pest Control in Push-Pull Intercropping Systems: What We Know, and Where to Go?

Push-pull technology (PPT) employs mixed cropping for sustainable intensification: an intercrop repels or suppresses pests of the focal crop (push), while a trap crop attracts pests out of the field (pull), where they may be targeted for control. Underlying chemical-ecological mechanisms have been demonstrated in controlled settings, primarily for some of the best-established cereal PPT systems developed in east Africa. Yet, many questions remain regarding mechanisms, and strategies to adapt PPT for different crops and locations. We conducted a systematic review of scientific literature on PPT and related practices for biological control of pests of food and fodder. Of 3335 results, we identified 45 reporting on chemistry of trap- or intercropping systems for pest control, of which 30 focused on cereals or African pests. Seven of these reported primary chemical data: measurements from glasshouse and laboratory studies (5), or of field-collected samples (2). From these 30, we provide a database of compounds, discussing degrees of evidence for their mediation of push-pull. We depict hypothesized spatial distributions of selected compounds in PPT fields from physical properties and emission/exudation rates, and design of the east African cereal PPT system, and discuss influences on activity in field settings likely to affect success

Natural variation in linalool metabolites: One genetic locus, many functions?

The ubiquitous volatile linalool is metabolized in plants to nonvolatile derivatives. We studied Nicotiana attenuata plants which naturally vary in (S)‐(+)‐linalool contents, and lines engineered to produce either (R)‐(‐)‐ or (S)‐(+)‐linalool. Only (S)‐(+)‐linalool production was associated with slower growth of a generalist herbivore, and a large fraction was present as nonvolatile derivatives. We found that variation in volatile linalool and its nonvolatile glycosides mapped to the same genetic locus which harbored the biosynthetic gene, NaLIS, but that free linalool varied more in environmental responses. This study reveals how (S)‐(+)‐linalool and conjugates differ in their regulation and possible functions in resistance

Screening of leaf extraction and storage conditions for eco‐metabolomics studies

Mass spectrometry‐based plant metabolomics is frequently used to identify novel natural products or study the effect of specific treatments on a plant's metabolism. Reliable sample handling is required to avoid artifacts, which is why most protocols mandate shock freezing of plant tissue in liquid nitrogen and an uninterrupted cooling chain. However, the logistical challenges of this approach make it infeasible for many ecological studies. Especially for research in the tropics, permanent cooling poses a challenge, which is why many of those studies use dried leaf tissue instead. We screened a total of 10 extraction and storage approaches for plant metabolites extracted from maize leaf tissue across two cropping seasons to develop a methodology for agroecological studies in logistically challenging tropical locations. All methods were evaluated based on changes in the metabolite profile across a 2‐month storage period at different temperatures with the goal of reproducing the metabolite profile of the living plant as closely as possible. We show that our newly developed on‐site liquid–liquid extraction protocol provides a good compromise between sample replicability, extraction efficiency, material logistics, and metabolite profile stability. We further discuss alternative methods which showed promising results and feasibility of on‐site sample handling for field studies

A novel synthesis of two decades of microsatellite studies on European beech reveals decreasing genetic diversity from glacial refugia

Genetic diversity influences the evolutionary potential of forest trees under changing environmental conditions, thus indirectly the ecosystem services that forests provide. European beech (Fagus sylvatica L.) is a dominant European forest tree species that increasingly suffers from climate change-related die-back. Here, we conducted a systematic literature review of neutral genetic diversity in European beech and created a meta-data set of expected heterozygosity (He) from all past studies providing nuclear microsatellite data. We propose a novel approach, based on population genetic theory and a min–max scaling to make past studies comparable. Using a new microsatellite data set with unprecedented geographic coverage and various re-sampling schemes to mimic common sampling biases, we show the potential and limitations of the scaling approach. The scaled meta-dataset reveals the expected trend of decreasing genetic diversity from glacial refugia across the species range and also supports the hypothesis that different lineages met and admixed north of the European mountain ranges. As a result, we present a map of genetic diversity across the range of European beech which could help to identify seed source populations harboring greater diversity and guide sampling strategies for future genome-wide and functional investigations of genetic variation. Our approach illustrates how to combine information from several nuclear microsatellite data sets to describe patterns of genetic diversity extending beyond the geographic scale or mean number of loci used in each individual study, and thus is a proof-of-concept for synthesizing knowledge from existing studies also in other species

Effects of atmospheric, topographic, and BRDF correction on imaging spectroscopy-derived data products

Surface reflectance is an important data product in imaging spectroscopy for obtaining surface information. The complex retrieval of surface reflectance, however, critically relies on accurate knowledge of atmospheric absorption and scattering, and the compensation of these effects. Furthermore, illumination and observation geometry in combination with surface reflectance anisotropy determine dynamics in retrieved surface reflectance not related to surface absorption properties. To the best of authors’ knowledge, no comprehensive assessment of the impact of atmospheric, topographic, and anisotropy effects on derived surface information is available so far.This study systematically evaluates the impact of these effects on reflectance, albedo, and vegetation products. Using three well-established processing schemes (ATCOR F., ATCOR R., and BREFCOR), high-resolution APEX imaging spectroscopy data, covering a large gradient of illumination and observation angles, are brought to several processing states, varyingly affected by mentioned effects. Pixel-wise differences of surface reflectance, albedo, and spectral indices of neighboring flight lines are quantitatively analyzed in their respective overlapping area. We found that compensation of atmospheric effects reveals actual anisotropy-related dynamics in surface reflectance and derived albedo, related to an increase in pixel-wise relative reflectance and albedo differences of more than 40%. Subsequent anisotropy compensation allows us to successfully reduce apparent relative reflectance and albedo differences by up to 20%. In contrast, spectral indices are less affected by atmospheric and anisotropy effects, showing relative differences of 3% to 10% in overlapping regions of flight lines.We recommend to base decisions on the use of appropriate processing schemes on individual use cases considering envisioned data products

Evaluating potential of leaf reflectance spectra to monitor plant genetic variation

Remote sensing of vegetation by spectroscopy is increasingly used to characterize trait distributions in plant communities. How leaves interact with electromagnetic radiation is determined by their structure and contents of pigments, water, and abundant dry matter constituents like lignins, phenolics, and proteins. High-resolution ("hyperspectral") spectroscopy can characterize trait variation at finer scales, and may help to reveal underlying genetic variation-information important for assessing the potential of populations to adapt to global change. Here, we use a set of 360 inbred genotypes of the wild coyote tobacco Nicotiana attenuata: wild accessions, recombinant inbred lines (RILs), and transgenic lines (TLs) with targeted changes to gene expression, to dissect genetic versus non-genetic influences on variation in leaf spectra across three experiments. We calculated leaf reflectance from hand-held field spectroradiometer measurements covering visible to short-wave infrared wavelengths of electromagnetic radiation (400-2500 nm) using a standard radiation source and backgrounds, resulting in a small and quantifiable measurement uncertainty. Plants were grown in more controlled (glasshouse) or more natural (field) environments, and leaves were measured both on- and off-plant with the measurement set-up thus also in more to less controlled environmental conditions. Entire spectra varied across genotypes and environments. We found that the greatest variance in leaf reflectance was explained by between-experiment and non-genetic between-sample differences, with subtler and more specific variation distinguishing groups of genotypes. The visible spectral region was most variable, distinguishing experimental settings as well as groups of genotypes within experiments, whereas parts of the short-wave infrared may vary more specifically with genotype. Overall, more genetically variable plant populations also showed more varied leaf spectra. We highlight key considerations for the application of field spectroscopy to assess genetic variation in plant populations

Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing

Plant ecology and biodiversity research have increasingly incorporated trait-based approaches and remote sensing. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on airborne LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait–trait relationships and functional diversity metrics obtained by the ITC- and pixel-based approaches at changing pixel size and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by airborne Pushbroom Hyperspectral Imager-3 (PHI-3) hyperspectral data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC-based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness also decreased with increasing pixel size, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, high-resolution pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage