Coconut Tree Stress Detection as an Indicator of Red Palm Weevil (RPW) Attack Using Sentinel Data

The red palm weevil (RPW) is one of the worst destructive pests of palms in the world. This study focuses for the first time on the coconut tree stress detection and discrimination among different stages of red palm weevil (RPW) stress-attacks using vegetation indices (VI) and the percentage of accuracy assessed. Different spectral indices were assessed using Sentinel 2A data of year 2018. Based on field identification, four classes of coconut tree were considered and evaluated using visual maps of VI: severe, moderate, early and healthy coconut trees. Results showed that the vegetation indices Normalized Differenced Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI), SQRT (IR/R), Difference Vegetation Index (DVI) and Green Vegetation Index (GVI) are sensitive to coconut trees caused by RPW attacks. They discriminated among the considered classes with more than 50% accurate from census data of field observation compared with remote sensing data of Sentinel 2A image. Nevertheless, they express the healthiness of tree stress between 0.308 – 0.673 range with 55% to 91% accurate. According to these results, it was concluded that remote sensing technique using Sentinel 2A data is a promising alternative for RPW detection based on VI.

The PalERF109 transcription factor positively regulates salt tolerance via PalHKT1;2 in Populus alba var. pyramidalis

Salinity restricts the growth of trees to varying extents, but the regulatory mechanisms involved in their varying salt tolerance are largely unknown. In an effort to elucidate these mechanisms, we identified a total of 99 genes in the Ethylene Responsive Factor (ERF) family of transcription factors and examined their expression patterns under salt stress in Populus alba var. pyramidalis. We found that a B4 group gene, PalERF109, was rapidly induced by salt treatment and preferentially expressed in stems and petioles, where it is probably involved in transport of ions and water in xylem. Overexpression of PalERF109 enhanced the salt tolerance of the poplar, and further analysis showed that it directly upregulated a high-affinity K+transporter (HKT) gene, PalHKT1;2. The results clearly indicate that PalERF109 enhances salt tolerance at least partially through direct activation of PalHKT1;2 and extends understanding of the roles of ERF genes in tree stress responses.

Spectral differentiation of oak wilt from foliar fungal disease and drought is correlated with physiological changes

Hyperspectral reflectance tools have been used to detect multiple pathogens in agricultural settings and single sources of infection or broad declines in forest stands. However, differentiation of any one disease from other sources of tree stress is integral for stand and landscape-level applications in mixed species systems. We tested the ability of spectral models to differentiate oak wilt, a fatal disease in oaks caused by Bretziella fagacearum ``Bretz'', from among other mechanisms of decline. We subjected greenhouse-grown oak seedlings (Quercus ellipsoidalis ``E.J. Hill'' and Quercus macrocarpa ``Michx.'') to chronic drought or inoculation with the oak wilt fungus or bur oak blight fungus (Tubakia iowensis ``T.C. Harr. & D. McNew''). We measured leaf and canopy spectroscopic reflectance (400–2400 nm) and instantaneous photosynthetic and stomatal conductance rates, then used partial least-squares discriminant analysis to predict treatment from hyperspectral data. We detected oak wilt before symptom appearance, and classified the disease with high accuracy in symptomatic leaves. Classification accuracy from spectra increased with declines in photosynthetic function in oak wilt-inoculated plants. Wavelengths diagnostic of oak wilt were only found in non-visible spectral regions and are associated with water status, non-structural carbohydrates and photosynthetic mechanisms. We show that hyperspectral models can differentiate oak wilt from other causes of tree decline and that detection is correlated with biological mechanisms of oak wilt infection and disease progression. We also show that within the canopy, symptom heterogeneity can reduce detection, but that symptomatic leaves and tree canopies are suitable for highly accurate diagnosis. Remote application of hyperspectral tools can be used for specific detection of disease across a multi-species forest stand exhibiting multiple stress symptoms.

Shifted phenology in the pine processionary moth affects the outcome of tree–insect interaction

In the Mediterranean and temperate regions, an increase in the frequency and intensity of drought events has been recorded, probably due to climate change. In consequence, trees will more frequently experience hydric stress, a condition that can be expected to affect insect–tree interactions, while adaptation mechanisms may be further in course. The effect of tree water stress on the performance of two allochronic populations of Thaumetopoea pityocampa was here studied. Namely, we compared a unique population of this insect, in which the larvae develop in the summer (SP), with the typical population having winter larval development (WP), to test the adaptation hypothesis to host plant status. Larvae of each population were fed on needles of young potted Pinus pinaster plants under two water supply regimes: (i) well-watered (control) and (ii) subjected to 3 months of drought stress. Compared to control, stressed plants had higher amounts of soluble sugars, phenols, and higher C/N ratio, whereas water content and chlorophylls concentrations were lower. In general, T. pityocampa larvae had lower performances on water-stressed plants, as shown by lower survival rates, lower needle consumption, and longer development times. Yet, the detrimental effects of tree stress were only significant for the WP larvae, while SP larvae were able to overcome such conditions. Results demonstrate that tree water stress can negatively affect T. pityocampa populations. Furthermore, the evidence is also provided that responses to the physiological condition of the host trees may occur at the population level, as a result of adaptation mechanisms driven by climate change.

Impervious Surface Thresholds and the Pace to Plant Technique for Planting Urban Red Maple Trees

A foundation of integrated pest management (IPM) in urban landscapes is to put the right plant in the right place. This preventive tactic can reduce plant stress, pest infestations, and subsequent pesticide applications. Many urban tree species have more insect and mite pests in urban landscapes than in surrounding natural areas. This is due in part to stress created by impervious surfaces, such as roads and sidewalks that can increase air temperature and reduce soil moisture. For red maples (Acer rubrum), more impervious surface area leads to more stress and worse tree condition. This publication focuses on selecting red maple planting sites that will help reduce tree stress and scale insect pests by maximizing surfaces permeable to water.

MEASURING LEAF WATER CONTENT USING MULTISPECTRAL TERRESTRIAL LASER SCANNING

Climate change is increasing the amount and intensity of disturbance events, i.e. drought, pest insect outbreaks and fungal pathogens, in forests worldwide. Leaf water content (LWC) is an early indicator of tree stress that can be measured remotely using multispectral terrestrial laser scanning (MS-TLS). LWC affects leaf reflectance in the shortwave infrared spectrum which can be used to predict LWC from spatially explicit MS-TLS intensity data. Here, we investigated the relationship between LWC and MS-TLS intensity features at 690 nm, 905 nm and 1550 nm wavelengths with Norway spruce seedlings in greenhouse conditions. We found that a simple ratio of 905 nm and 1550 nm wavelengths was able to explain 84 % of the variation (R2) in LWC with a respective prediction accuracy of 0.0041 g/cm². Our results showed that MS-TLS can be used to estimate LWC with a reasonable accuracy in environmentally stable conditions.