Do foliar anthocyanin pigments in horopito (Pseudowintera colorata) function as visual signals to deter insect herbivores?

<p>Anthocyanin pigments are synthesised in the leaves of many plants, however the adaptive significance of these pigments is not entirely understood. It has been postulated that their red colours may function as visual signals through coevolution between herbivorous insects and their host tree species, though the hypothesis lacks solid empirical evidence. I investigated the leaf signalling hypothesis using Pseudowintera colorata, focusing on five areas: 1) I exploited the natural polymorphism in leaf colour of P. colorata to test the predictions that (i) bright leaf colour is a reliable signal of a plant’s defensive commitment; (ii) insects in the field avoid trees that are brightly coloured; and (iii) the trees with the brightest leaves will have higher fitness. Relative to green leaves, redder foliage contained higher concentrations of polygodial, a sesquiterpene dialdehyde known to have strong antifeedant properties, and incurred less insect feeding damage. Redder trees hosted fewer Ctenopseustis spp. leafroller larvae than neighbouring matched green trees. Contrary to the predictions of the leaf signalling hypothesis, there was no difference in any of the measured fitness parameters between red and green trees, indicating that the leaf colour polymorphism in P. colorata is stable. 2) Many insects are sensitive to volatile organic compounds (VOCs), however the role of VOCs in plant-herbivore signalling has not been investigated. I analysed VOCs released from undamaged, herbivore- and mechanically-damaged red and green leaves of P. colorata, and the olfactory preferences of brownheaded leafroller (C. obliquana) larvae. While the VOC profiles of browsed and unbrowsed leaves were statistically distinguishable, the VOC profiles released from intact, herbivore-, and mechanically-damaged P. colorata leaves did not reliably identify leaf colour. Moreover, naïve and experienced C. obliquana larvae displayed no preference for the volatiles from mechanically-damaged red or green leaves. Therefore, I concluded that VOC compounds are not likely to play a large role in mediating insect herbivore-plant interactions in P. colorata. 3) Studies of leaf signalling rarely consider the influence of the light-absorbing properties of non-green pigments upon photosynthesis. I compared the photosynthetic and photoinhibitory responses of red and green leaves from matched, neighbouring pairs of P. colorata of contrasting colour. Redder P. colorata leaves in the field had a lower maximum photosynthetic assimilation rate than matched green leaves from neighbouring trees. However, I was unable to detect any measurable advantage in terms of photoprotection in the red P. colorata leaves as indicated by chlorophyll fluorescence profiles. My results indicate that the presence of anthocyanin pigments within non-senescing leaves may impose a slight photosynthetic cost to the plant. 4) I used literature searches, field surveys and laboratory bioassays to identify which invertebrate herbivores are most likely to participate in leaf-signalling interactions with P. colorata. Feeding preference bioassays showed that brownheaded leafrollers (C. obliquana and C. herana) and Auckland tree weta (Hemideina thoracica) preferentially consumed leaf material from green than red P. colorata leaves. Results from these bioassays, combined with my field surveys suggest that Ctenopseustis spp. leafroller larvae are the most likely coevolution partners for P. colorata. 5) There is a well-established link between nitrogen deficiency and leaf reddening. Additionally, leaf nutrients can influence foraging behaviour and performance of insect herbivores. I measured N and C contents of leaves from neighbouring matched pairs of red and green P. colorata. There were no significant differences in the amounts of, or ratio between, N and C between matched red and green leaves. This result indicates that differences in colour and herbivory among P. colorata leaves are not attributable to differences in leaf nutrients. Taken together, my results suggest that foliar anthocyanins in P. colorata do function as visual signals, however their effect on herbivory is small. Additionally, interindividual variation in non-senescing leaf colour in P. colorata may be stable due to a trade off between signalling and photosynthesis. Discussions of leaf signalling need to follow the examples of other fields studying the interactions between plants and insects and move from overly simple models to those that incorporate more of the complexity that is observed in the natural world.</p>

Do foliar anthocyanin pigments in horopito (Pseudowintera colorata) function as visual signals to deter insect herbivores?

<p>Anthocyanin pigments are synthesised in the leaves of many plants, however the adaptive significance of these pigments is not entirely understood. It has been postulated that their red colours may function as visual signals through coevolution between herbivorous insects and their host tree species, though the hypothesis lacks solid empirical evidence. I investigated the leaf signalling hypothesis using Pseudowintera colorata, focusing on five areas: 1) I exploited the natural polymorphism in leaf colour of P. colorata to test the predictions that (i) bright leaf colour is a reliable signal of a plant’s defensive commitment; (ii) insects in the field avoid trees that are brightly coloured; and (iii) the trees with the brightest leaves will have higher fitness. Relative to green leaves, redder foliage contained higher concentrations of polygodial, a sesquiterpene dialdehyde known to have strong antifeedant properties, and incurred less insect feeding damage. Redder trees hosted fewer Ctenopseustis spp. leafroller larvae than neighbouring matched green trees. Contrary to the predictions of the leaf signalling hypothesis, there was no difference in any of the measured fitness parameters between red and green trees, indicating that the leaf colour polymorphism in P. colorata is stable. 2) Many insects are sensitive to volatile organic compounds (VOCs), however the role of VOCs in plant-herbivore signalling has not been investigated. I analysed VOCs released from undamaged, herbivore- and mechanically-damaged red and green leaves of P. colorata, and the olfactory preferences of brownheaded leafroller (C. obliquana) larvae. While the VOC profiles of browsed and unbrowsed leaves were statistically distinguishable, the VOC profiles released from intact, herbivore-, and mechanically-damaged P. colorata leaves did not reliably identify leaf colour. Moreover, naïve and experienced C. obliquana larvae displayed no preference for the volatiles from mechanically-damaged red or green leaves. Therefore, I concluded that VOC compounds are not likely to play a large role in mediating insect herbivore-plant interactions in P. colorata. 3) Studies of leaf signalling rarely consider the influence of the light-absorbing properties of non-green pigments upon photosynthesis. I compared the photosynthetic and photoinhibitory responses of red and green leaves from matched, neighbouring pairs of P. colorata of contrasting colour. Redder P. colorata leaves in the field had a lower maximum photosynthetic assimilation rate than matched green leaves from neighbouring trees. However, I was unable to detect any measurable advantage in terms of photoprotection in the red P. colorata leaves as indicated by chlorophyll fluorescence profiles. My results indicate that the presence of anthocyanin pigments within non-senescing leaves may impose a slight photosynthetic cost to the plant. 4) I used literature searches, field surveys and laboratory bioassays to identify which invertebrate herbivores are most likely to participate in leaf-signalling interactions with P. colorata. Feeding preference bioassays showed that brownheaded leafrollers (C. obliquana and C. herana) and Auckland tree weta (Hemideina thoracica) preferentially consumed leaf material from green than red P. colorata leaves. Results from these bioassays, combined with my field surveys suggest that Ctenopseustis spp. leafroller larvae are the most likely coevolution partners for P. colorata. 5) There is a well-established link between nitrogen deficiency and leaf reddening. Additionally, leaf nutrients can influence foraging behaviour and performance of insect herbivores. I measured N and C contents of leaves from neighbouring matched pairs of red and green P. colorata. There were no significant differences in the amounts of, or ratio between, N and C between matched red and green leaves. This result indicates that differences in colour and herbivory among P. colorata leaves are not attributable to differences in leaf nutrients. Taken together, my results suggest that foliar anthocyanins in P. colorata do function as visual signals, however their effect on herbivory is small. Additionally, interindividual variation in non-senescing leaf colour in P. colorata may be stable due to a trade off between signalling and photosynthesis. Discussions of leaf signalling need to follow the examples of other fields studying the interactions between plants and insects and move from overly simple models to those that incorporate more of the complexity that is observed in the natural world.</p>

Short-Term Effects of Spent Mushroom Substrate Mulching Thickness on the Soil Environment, Weed Suppression, Leaf Nutrients, and Nut Characteristics in a Hazelnut Orchard

Worldwide, a huge amount of solid fermented waste is produced every year during mushroom production. The rational utilization of spent mushroom substrate (SMS) is conducive to environmental protection and the sustainable development of agriculture. The aims of this work were to analyze the effects of the SMS mulching thickness on the soil environment, weed suppression, leaf nutrients, and nut traits in a hazelnut plantation and provide a theoretical basis for the scientific and reasonable utilization of SMS. An SMS mulching experiment with four mulching thickness treatments (MT1: 5 cm, MT2: 10 cm, MT3: 15 cm, and CK: 0 cm) was conducted in a semi-arid area of North China in 2019. The soil properties, weed control efficiency, leaf nutrient content, and nut yield and quality characteristics of these treatments were all measured and analyzed. The results showed that (1) the average soil temperatures of MT2 and MT3 at different soil depths were 0.73–1.78 °C and 1.18–2.50 °C lower than when no mulch was used in warm weather and 0.67–1.05 °C and 0.99–1.56 °C higher than when no mulch was used in cold weather. The average soil moisture content of MT1, MT2, and MT3 at different soil depths was 6.27–8.13%, 10.66–17.23%, and 7.26–12.81% higher than that of CK, respectively. There were no significant differences in the soil bulk density or porosity among the four treatments. The average soil nutrient contents (soil organic matter and available N, P, and K) of MT1, MT2, and MT3 were 7.05–15.23%, 14.90–38.93%, and 17.42–40.11% higher than those of CK, respectively. Soil enzymatic activities of these treatments followed the order MT3 ≈ MT2 > MT1 > CK. (2) MT2 and MT3 both had high levels of weed control efficiency: 55.66–92.93% and 70.43–97.90%, respectively. (3) The leaf N, P, K, and SPAD increased significantly under MT2 and MT3 by about 10% compared with the CK. (4) MT2 effectively increased the nut size, nut and kernel mass, and crude fat content of the nut (CFC). In general, the short-term field experiment clearly showed that SMS is a superior mulching material for improving the soil environment and plant growth, and 10 cm thickness is suitable for mulching practice.

Soil and Leaf Nutrients Drivers on the Chemical Composition of the Essential Oil of Siparuna muricata (Ruiz & Pav.) A. DC. from Ecuador

Chemical compositions of plants are affected by the initial nutrient contents in the soil and climatic conditions; thus, we analyzed for the first time the effects of soil and leaf nutrients on the compositions of the essential oils (EOs) of Siparuna muricata in four different localities in Ecuador. EOs were obtained by hydrodistillation and analyzed by gas chromatography/mass spectrometry (GC/MS) and a gas chromatography/flame ionization detector (GC/FID). Enantiomeric distribution by GC/MS was determined, modifying the enantiomeric separation of β-pinene, limonene, δ-elemene, β-bourbonene, cis-cadina-1 (6), 4-diene and atractylone. A total of 44 compounds were identified. The most representative for L1 were guaiol, atractylone and 4-diene; for L2, cis-cadina-1(6),4-diene and myrcene; for L3, atractylone, myrcene and germacrene B; and finally, L4 germacrene B, myrcene and cis-cadina-1(6),4-diene. Correlations between soil- leaf chemical elements such as Al, Ca, Fe, Mg, Mn, N and Si in the different localities were significant with chemical composition of the essential oil of Siparuna muricata; however, correlations between soil and leaf K, P, and Na were not significant. Cluster and NMDS analysis showed high dissimilarity values of secondary metabolites between four localities related with changes in soil- leaf nutrients. Thus, the SIMPER routine revealed that not all secondary metabolites contribute equally to establishing the differences in the four localities, and the largest contributions are due to differences in guaiol, cis-cadina-1(6),4-diene, atractylone and germacrene. Our investigation showed for the first time the influences of altitude and soil- leaf chemical elements in the chemical composition of the EOs of S. muricata.

Monitoring the Foliar Nutrients Status of Mango Using Spectroscopy-Based Spectral Indices and PLSR-Combined Machine Learning Models

Conventional methods of plant nutrient estimation for nutrient management need a huge number of leaf or tissue samples and extensive chemical analysis, which is time-consuming and expensive. Remote sensing is a viable tool to estimate the plant’s nutritional status to determine the appropriate amounts of fertilizer inputs. The aim of the study was to use remote sensing to characterize the foliar nutrient status of mango through the development of spectral indices, multivariate analysis, chemometrics, and machine learning modeling of the spectral data. A spectral database within the 350–1050 nm wavelength range of the leaf samples and leaf nutrients were analyzed for the development of spectral indices and multivariate model development. The normalized difference and ratio spectral indices and multivariate models–partial least square regression (PLSR), principal component regression, and support vector regression (SVR) were ineffective in predicting any of the leaf nutrients. An approach of using PLSR-combined machine learning models was found to be the best to predict most of the nutrients. Based on the independent validation performance and summed ranks, the best performing models were cubist (R2 ≥ 0.91, the ratio of performance to deviation (RPD) ≥ 3.3, and the ratio of performance to interquartile distance (RPIQ) ≥ 3.71) for nitrogen, phosphorus, potassium, and zinc, SVR (R2 ≥ 0.88, RPD ≥ 2.73, RPIQ ≥ 3.31) for calcium, iron, copper, boron, and elastic net (R2 ≥ 0.95, RPD ≥ 4.47, RPIQ ≥ 6.11) for magnesium and sulfur. The results of the study revealed the potential of using hyperspectral remote sensing data for non-destructive estimation of mango leaf macro- and micro-nutrients. The developed approach is suggested to be employed within operational retrieval workflows for precision management of mango orchard nutrients.