Spectroscopic detection of forest diseases: a review (1970–2020)

Sustainable forest management is essential to confront the detrimental impacts of diseases on forest ecosystems. This review highlights the potential of vegetation spectroscopy in improving the feasibility of assessing forest disturbances induced by diseases in a timely and cost-effective manner. The basic concepts of vegetation spectroscopy and its application in phytopathology are first outlined then the literature on the topic is discussed. Using several optical sensors from leaf to landscape-level, a number of forest diseases characterized by variable pathogenic processes have been detected, identified and quantified in many country sites worldwide. Overall, these reviewed studies have pointed out the green and red regions of the visible spectrum, the red-edge and the early near-infrared as the spectral regions most sensitive to the disease development as they are mostly related to chlorophyll changes and symptom development. Late disease conditions particularly affect the shortwave-infrared region, mostly related to water content. This review also highlights some major issues to be addressed such as the need to explore other major forest diseases and geographic areas, to further develop hyperspectral sensors for early detection and discrimination of forest disturbances, to improve devices for remote sensing, to implement long-term monitoring, and to advance algorithms for exploitation of spectral data. Achieving of these goals will enhance the capability of vegetation spectroscopy in early detection of forest stress and in managing forest diseases.

Maximum Entropy Modeling to Predict the Impact of Climate Change on Pine Wilt Disease in China

Pine wilt disease is a devastating forest disease caused by the pinewood nematode Bursaphelenchus xylophilus, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and B. xylophilus in China. Further, the potential distribution was modeled using the current (1970–2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees’ distribution, while those related to precipitation affected B. xylophilus’s distribution. In the future, the suitable area of B. xylophilus will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and B. xylophilus will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face B. xylophilus threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of B. xylophilus.

Estimating the abundance of the typographer bark beetle in the spruce forests of the Republic of Tatarstan

The article provides an estimation of abundance the typographer bark beetle using barrier traps in the spruce forests of the Republic of Tatarstan. For the last 10 years, there has been the shrinkage of spruce forests throughout the Russian Federation due to adverse factors, primarily the weather. In the forests of the Republic of Tatarstan, the main reasons for the unsatisfactory condition of forest stands are forest diseases – 20,276.7 ha and weather conditions – 16,824.1 ha, corresponding to 51.7% and 42.9% of the area of all plantations with disrupted and lost stability. The research studies were carried out in the “Sabinskiy Forestry Enterprise” and “Lubyankskiy Forestry Enterprise” of the Republic of Tatarstan. According to our observations for the whole growing season, the largest number of beetles is concentrated on a site of pure plantings at the age of 40 years and is estimated at 1,645 pcs. On all three sites, the peak number of beetles takes place on July 5, 2019 corresponding to 3,684 pcs. In 2019, there was damping of some foci of this pest on 330.1 ha. At the same time, the new foci were identified, which accounted for 9.5% of the total area of bark beetle foci. As a result, at the end of 2019, the total area of foci of this pest in the forests of the Republic of Tatarstan was 1,018.9 ha, which is 28% less than the same indicator last year.

Pine Pitch Canker (PPC): Pathways of Pathogen Spread and Preventive Measures

Fusarium circinatum (Nirenberg and O’ Donnell) is the causal agent of pine pitch canker (PPC) disease, one of the most devastating forest diseases worldwide. Long-distance spread occurs mainly through the movement of infected seeds whereas at regional level, the movement of seedlings, substrates, or containers may play an important role in fungal dispersal. Invasion of nurseries takes place via infected seeds and further spread can occur by planting contaminated seedlings, especially due to the possibility of infected plants remaining symptomless. Once established, F. circinatum spreads by rain, wind, and insects. The natural spread of the pathogen is limited due to the short dispersal distances of the spores and the fairly short flight distances of disseminating insects. In this review, we summarize the currently known dispersal pathways of the pathogen, discussing both natural and human-assisted processes. With the purpose of understanding how to best intervene in the disease’s development in nurseries and forests, we outline the epidemiology of the pathogen describing the key factors influencing its spread. Preventive measures to control the spread of F. circinatum locally and globally are described with special emphasis on the challenges in implementing them.

Interacting Effects of Global Change on Forest Pest and Pathogen Dynamics

Pathogens and insect pests are important drivers of tree mortality and forest dynamics, but global change has rapidly altered or intensified their impacts. Predictive understanding of changing disease and outbreak occurrence has been limited by two factors: ( a) tree mortality and morbidity are emergent phenomena determined by interactions between plant hosts, biotic agents (insects or pathogens), and the environment; and ( b) disparate global change drivers co-occur, obscuring net impacts on each of these components. To expand our understanding of changing forest diseases, declines, and outbreaks, we adopt a framework that identifies and organizes observed impacts of diverse global change drivers on the primary mechanisms underlying agent virulence and host susceptibility. We then discuss insights from ecological theory that may advance prediction of forest epidemics and outbreaks. This approach highlights key drivers of changing pest and pathogen dynamics, which may inform forest management aimed at mitigating accelerating rates of tree mortality globally.

Mapping the Potential Distribution of Oak Wilt (Bretziella fagacearum) in East Central and Southeast Minnesota Using Maxent

With the advancement of spatial analysis and remote sensing technology, potentially devastating forest pathogens can be managed through spatial modeling. This study used Maxent, a presence-only species-distribution model, to map the potential probability distribution of the invasive forest pathogen oak wilt (Bretziella fagacearum) in eastern and southeastern Minnesota. The model related oak wilt occurrence data to environmental variables including climate, topography, land cover, soil, and population density. Results showed that areas with the highest probability of oak wilt occur within and surrounding the Minneapolis/St. Paul metropolitan area. The jackknife test of variable importance indicated land cover and soil type as important variables contributing to the prediction of the distribution. Multiple methods of analysis showed that the model performed better than random at predicting the occurrence of oak wilt. This study shows Maxent’s potential as an accurate tool in the early detection and management of forest diseases.