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The introduction of wood-boring insects to non-native areas can pose a significant threat to global forest ecosystems. Aromia bungii and Massicus raddei, native to Asia including Korea but potentially important in urban forestry worldwide, are severe trunk borers that have recently infested host trees in urban landscapes of Korea. The signs of external injury can help identify cerambycid-infested trees. However, assessing the internal condition of trees without causing damage is challenging, which hinders the management of infested trees that are still alive. This study evaluated the potential use of sonic tomography to assess injury characteristics in the woody parts of trees, such as Prunus × yedoensis and Quercus palustris infested by A. bungii and M. raddei, respectively. Among the 45 investigated trees, the number of holes on external parts was recorded by visual examination. Sonic tomography images revealed decayed areas, allowing for a comparison of internal damage between infested and non-infested trees. The internal status of trees infested by the two cerambycid beetles differed from that of healthy trees. While some healthy trees exhibited minimal internal damage, those that were not infested by beetles showed decayed areas, potentially caused by non-biological factors such as frozen cracks. In conclusion, sonic tomography equipment can potentially be used for non-invasive assessment of internal injuries caused by wood-boring insects in urban trees. [ABSTRACT FROM AUTHOR]

We present an evaluation of different deep learning and machine learning approaches for tree health classification in the Black Forest, the Harz Mountains, and the Göttinger Forest on a unique, highly accurate tree-level dataset. The multispectral UAV data were collected from eight forest plots with diverse tree species, mostly conifers. As ground truth data (GTD), nearly 1500 tree polygons with related attribute information on the health status of the trees were used. This data were collected during extensive fieldwork using a mobile application and subsequent individual tree segmentation. Extensive preprocessing included normalization, NDVI calculations, data augmentation to deal with the underrepresented classes, and splitting the data into training, validation, and test sets. We conducted several experiments using a classical machine learning approach (random forests), as well as different convolutional neural networks (CNNs)—ResNet50, ResNet101, VGG16, and Inception-v3—on different datasets and classes to evaluate the potential of these algorithms for tree health classification. Our first experiment was a binary classifier of healthy and damaged trees, which did not consider the degree of damage or tree species. The best results of a 0.99 test accuracy and an F1 score of 0.99 were obtained with ResNet50 on four band composites using the red, green, blue, and infrared bands (RGBI images), while VGG16 had the worst performance, with an F1 score of only 0.78. In a second experiment, we also distinguished between coniferous and deciduous trees. The F1 scores ranged from 0.62 to 0.99, with the highest results obtained using ResNet101 on derived vegetation indices using the red edge band of the camera (NDVIre images). Finally, in a third experiment, we aimed at evaluating the degree of damage: healthy, slightly damaged, and medium or heavily damaged trees. Again, ResNet101 had the best performance, this time on RGBI images with a test accuracy of 0.98 and an average F1 score of 0.97. These results highlight the potential of CNNs to handle high-resolution multispectral UAV data for the early detection of damaged trees when good training data are available. [ABSTRACT FROM AUTHOR]

The widespread tree mortality caused by the European spruce bark beetle (Ips typographus L.) is a significant concern for Norway spruce-dominated (Picea abies H. Karst) forests in Europe and there is evidence of increases in the affected areas due to climate warming. Effective forest monitoring methods are urgently needed for providing timely data on tree health status for conducting forest management operations that aim to prepare and mitigate the damage caused by the beetle. Unoccupied aircraft systems (UASs) in combination with machine learning image analysis have emerged as a powerful tool for the fast-response monitoring of forest health. This research aims to assess the effectiveness of deep neural networks (DNNs) in identifying bark beetle infestations at the individual tree level from UAS images. The study compares the efficacy of RGB, multispectral (MS), and hyperspectral (HS) imaging, and evaluates various neural network structures for each image type. The findings reveal that MS and HS images perform better than RGB images. A 2D-3D-CNN model trained on HS images proves to be the best for detecting infested trees, with an F1-score of 0.759, while for dead and healthy trees, the F1-scores are 0.880 and 0.928, respectively. The study also demonstrates that the tested classifier networks outperform the state-of-the-art You Only Look Once (YOLO) classifier module, and that an effective analyzer can be implemented by integrating YOLO and the DNN classifier model. The current research provides a foundation for the further exploration of MS and HS imaging in detecting bark beetle disturbances in time, which can play a crucial role in forest management efforts to combat large-scale outbreaks. The study highlights the potential of remote sensing and machine learning in monitoring forest health and mitigating the impacts of biotic stresses. It also offers valuable insights into the effectiveness of DNNs in detecting bark beetle infestations using UAS-based remote sensing technology. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate fungal communities associated with leaves and roots of healthy-looking and declining U. glabra trees. The study was expected to demonstrate whether and how the diversity and composition of fungal communities change in these functional tissues following the infection by Dutch elm disease-causing fungi. The study sites included six U. glabra sites in Lithuania, where leaves and roots were sampled. DNA was isolated from individual samples, amplified using ITS2 rRNA as a marker, and subjected to high-throughput sequencing. The sequence analysis showed the presence of 32,699 high-quality reads, which following clustering, were found to represent 520 non-singleton fungal taxa. In leaves, the fungal species richness was significantly higher in healthy-looking trees than in diseased ones (p < 0.05). In roots, a similar comparison showed that the difference was insignificant (p > 0.05). The most common fungi in all samples of roots were Trichocladium griseum (32.9%), Penicillium restrictum (21.2%), and Unidentified sp. 5238_7 (12.6%). The most common fungi in all samples of leaves were Trichomerium sp. 5238_8 (12.30%), Aureobasidium pullulans (12.03%), Cladosporium sp. 5238_5 (11.73%), and Vishniacozyma carnescens (9.86%). The results showed that the detected richness of fungal taxa was higher in samples collected from healthy-looking trees than from diseased ones, thereby highlighting the negative impact of the Dutch elm disease on the overall fungal diversity. [ABSTRACT FROM AUTHOR]

Climate change, which leads to higher temperatures, droughts, and storms, is expected to have a strong effect on both health of forest trees and associated biodiversity. The aim of this study was to investigate the diversity and composition of fungal communities associated with the functional tissues and rhizosphere soil of healthy-looking Picea abies to better understand these fungal communities and their potential effect on tree health in the process of climate change. The study sites included 30 P. abies stands, where needles, shoots, roots, and the rhizosphere soil was sampled. DNA was isolated from individual samples, amplified using ITS2 rRNA as a marker and subjected to high-throughput sequencing. The sequence analysis showed the presence of 232,547 high-quality reads, which following clustering were found to represent 2701 non-singleton fungal OTUs. The highest absolute richness of fungal OTUs was in the soil (1895), then in the needles (1049) and shoots (1002), and the lowest was in the roots (641). The overall fungal community was composed of Ascomycota (58.3%), Basidiomycota (37.2%), Zygomycota (2.5%), Chytridiomycota (1.6%), and Glomeromycota (0.4%). The most common fungi based on sequence read abundance were Aspergillus pseudoglaucus (7.9%), Archaeorhizomyces sp. (3.6%), and Rhinocladiella sp. (2.0%). Pathogens were relatively rare, among which the most common were Phacidium lacerum (1.7%), Cyphellophora sessilis (1.4%), and Rhizosphaera kalkhoffii (1.4%). The results showed that the detected diversity of fungal OTUs was generally high, but their relative abundance varied greatly among different study sites, thereby highlighting the complexity of interactions among the host trees, fungi, and local environmental conditions. [ABSTRACT FROM AUTHOR]

Policy makers are challenged to find ways of influencing and supporting land manager behaviours and actions to deal with the impacts of increasing pressure from tree pests and diseases. This paper investigates attitudes and behaviours of farmers towards managing trees on farmland for pests and diseases. Data collection with farmers included deliberative workshops and semi-structured interviews. Data were thematically analyzed using the COM-B (Capacity/Opportunity/Motivation-Behaviour) model to understand the drivers of farmer behaviour for tree health. Results suggested farmers had some knowledge, experience and skills managing trees, but they did not recognize this capacity. Social norms and networks impacted the context of opportunity to act for tree health, along with access to trusted advice and labour, and the costs associated with management action. Motivational factors such as self-efficacy, perceived benefits of acting, personal interest and sense of agency were impacted by farmers' self-identity as food producers. The COM-B model also provides a framework for identifying intervention design through a Behaviour Change Wheel. This suggests that enhancing self-efficacy supported by the right kind of advice and guidance, framed and communicated in farmers' terms and brokered by appropriate knowledge intermediaries, seems critical to building action amongst different farmer types and attitudinal groups. [ABSTRACT FROM AUTHOR]

The concern for the fate of forest ecosystems under climate change demands the development of a prompt and effective system for detecting the impacts of pressure factors, such as rising temperatures, drought conditions, and extreme climatic events. In ongoing European monitoring programs, the health condition of trees is only assessed visually as a matter of course and there is limited evidence that enhanced crown defoliation implies physiological disturbance and reduced tree growth. The progress of the research makes it possible to apply methods developed in experimental conditions in forests for the fast and reliable assessment of impacts and of stress conditions. In this review, we analyze the most promising indicators of tree and forest health (at individual plant and ecosystem levels) for their potential application in forest ecosystems and their ability to support and integrate the traditional visual assessment, provide information on influential factors, and improve the prediction of stand dynamics and forest productivity. [ABSTRACT FROM AUTHOR]

Forest nurseries in Sweden produce ca. 360 million seedlings of Pinus sylvestris L. and Picea abies (L.) Karst. annually. Fungi represent the largest microbial component in rhizospheres and may significantly affect health and, consequently, quality of the seedlings. The aim of this study was to assess fungi focusing on pathogens in roots and the sphagnum peat growth substrate of healthy-looking P. sylvestris and P. abies seedlings from nine forest nurseries situated in northern, central and southern regions of Sweden. We hypothesized that nursery stock and the growth substrate can provide a venue for dissemination of fungal diseases. In each nursery and for each tree species, 100 seedlings with the growth substrate were collected during the dormant period. DNA was isolated from parts of root systems and from samples of the growth substrate, amplified using internal transcribed spacer of rDNA as a marker and 454-sequenced. Clustering at 98.5% similarity of 169,844 high-quality sequences resulted in 619 non-singleton fungal taxa. Although results showed that management practices in forest nurseries generally give a healthy stock, latent establishment of pathogenic fungi in both roots and the growth substrate supported the hypothesis. Furthermore, seedling roots and the growth substratewere inhabited by distinct communities of fungi, and lifestyles of these fungi largely determined community segregation into particular ecological niche. [ABSTRACT FROM AUTHOR]

The invasive woodwasp Sirex noctilio (Hymenoptera: Siricidae) is established in east-central North America. A replicated case study testing the effectiveness of silvicultural treatments for reducing the number of S. noctilio attacked trees in a stand was conducted in New York, USA. Silvicultural treatments reduced S. noctilio attacked trees by approximately 75% over the course of the study. There was no tree growth response to silvicultural treatments in the four years after thinning, but targeted removal of weakened trees removed potential S. noctilio habitat from treated stands. Two spectral vegetation indices were used to determine tree health in each treatment and potentially provide guidance for detection efforts. Silvicultural treatment significantly influenced the Red Edge Inflection Point, a strong indicator of chlorophyll content, and the Moisture Stress Index, a reflectance measurement sensitive to changes in foliar leaf water content, with the greatest differences occurring between control and treated blocks. Vegetation indices showed promise as a tool for aiding in stand prioritization for S. noctilio surveys or management activities. [ABSTRACT FROM AUTHOR]

Botryosphaeriaceae represents a diverse family of fungi with a cosmopolitan distribution and a wide host range. We studied species diversity and overlap of Botryosphaeriaceae on selected tree species of Anacardiaceae in disturbed (farming or forestry) and undisturbed (isolated and/or protected) ecosystems in the Limpopo and Mpumalanga provinces, South Africa. The disturbed sites resided at Tshikundamalema and Tshipise in Limpopo and the undisturbed sites at Nwanedi and the Mapungubwe National Park in Limpopo and the Kruger National Park in Mpumalanga. Asymptomatic branches were collected from Mangifera indica, Sclerocarya birrea and Lannea schweinfurthii trees in 2017 and 2018. Eleven species were identified using a multi-gene sequencing approach, including Diplodia allocellula, Dothiorella brevicollis, Do. dulcispinae, Do. viticola, Lasiodiplodia crassispora, L. exigua, L. gonubiensis, L. mahajangana, Neofusicoccum parvum, Oblongocollomyces sp. 1 and Oblongocollomyces sp. 2. Ten of the 11 species were identified in undisturbed ecosystems (eight species being unique), while only three species were identified in disturbed ecosystems (one species being unique). Two species were generalists on trees in disturbed and undisturbed ecosystems. Lasiodiplodia mahajangana was the most dominant species as it occurred on the three tree species of Anacardiaceae. Isolates of N. parvum occurred on both S. birrea (a native species) and M. indica (a non-native species) that occurred adjacent to each other in disturbed ecosystems, confirming the ability of this invasive pathogen to cross-infect native and non-native hosts and its abundance in human-disturbed environments. The findings from this study confirm the lack of host specificity for most species of Botryosphaeriaceae. The results also indicate that disturbance through human activity, such as clear-cutting, selective cutting and land-use changes, negatively influences the diversity of the Botryosphaeriaceae. [ABSTRACT FROM AUTHOR]

Forests worldwide are facing increasing pressures, with human travel and trade assisting the spread of pests and diseases. Climate change is likely to enhance the negative impacts of pests and diseases, which cause global declines and local extinctions. In this research we focus on three local and regional knowledge networks in the UK concerned with pests and diseases to explore to what extent the networks raise awareness and encourage other actions in their members, and identify what roles social capital and social learning play in these networks. A qualitative approach was undertaken. Three networks focused on pests and diseases were studied in the research, which involved 20 interviews with network members, and in situ discussions with two of the networks involving 41 members. Interviewees in the networks self-reported increased awareness and understanding of tree health issues as an important outcome of their participation in a network. The networks engaged in a range of actions, from knowledge exchange to developing guidance and running events, workshops and field trips. The role of the networks in supporting the development of social capital and social learning made an important contribution to the knowledge exchange and other actions undertaken, and highlights how networks can contribute to landscape-level action towards tree health. Stakeholders need to be included in responses to pest and disease threats, and networks can play an important role in raising awareness, knowledge exchange and linking up diverse land managers. This research provides evidence of the importance of networks in developing a collective approach, creating a stronger voice, aiding different organisations and individuals to work together, and providing an arena for social learning and developing useful relationships. A recognition of the importance of networks and the provision of some financial support could aid their continuation. [ABSTRACT FROM AUTHOR]

Forest decline diseases are complex processes driven by biotic and abiotic factors. Although information about host–microbiome–environment interactions in agricultural systems is emerging rapidly, similar studies on tree health are still in their infancy. We used acute oak decline (AOD) as a model system to understand whether the rhizosphere physicochemical properties and microbiome are linked to tree health by studying these two factors in healthy and diseased trees located in three sites in different AOD stages—low, mid and severe. We found significant changes in the rhizosphere properties and microbiome composition across the different AOD sites and between the tree health conditions. Rhizosphere pH correlated with microbiome composition, with the microbial assemblages changing in more acidic soils. At the severe AOD site, the oak trees exhibited the lowest rhizosphere pH and distinct microbiome, regardless of their health condition, whereas, at the low and mid-stage AOD sites, only diseased trees showed lower pH and the microbial composition differed significantly from healthy trees. On these two sites, less extreme soil conditions and a high presence of host-beneficial microbiota were observed in the healthy oak trees. For the first time, this study gathers evidence of associations among tree health conditions, rhizosphere properties and microbiome as well as links aboveground tree decline symptoms to the belowground environment. This provides a baseline of rhizosphere community profiling of UK oak trees and paves the way for these associations to be investigated in other tree species suffering decline disease events. [ABSTRACT FROM AUTHOR]

Tree and forest health is increasingly influenced by climate change as well as growing globalisation and trade. Climate change enables species to colonise new environments, and species that previously were constrained by native predators are now able to flourish in these new environments with little or no resistance. Additionally, the growing trade in live plants and wood products results in the inadvertent movement of species (such as pests or fungi in soil) from far away areas of the globe. As a result, new forest and tree risks may occur with the potential for significant impacts on forest and tree health. However, managing these impacts through legislation and policy is a challenge, particularly in terms of balancing a predominant free trade policy alongside substantial biosecurity concerns. This Special Issue highlights the social system considerations around forest health: the ways in which specific legislative and policy systems, at the national, regional or local level, aim at regulating or managing increasing invasive species risks and outbreak events; the ways in which policy instruments, technologies or management practices can be developed to manage tree pests and pathogens; and the socioeconomic and cultural implications of pest or disease outbreaks. It illustrates the possibilities and limitations in specific socioeconomic and political systems to manage and limit the impacts of increasing challenges to forest health under climate change and globalisation. [ABSTRACT FROM AUTHOR]

Simple Summary: The impact on tree health from insect pests and microbial diseases that have moved across country borders has been increasing in recent years. This poses a significant challenge to government authorities, and a number of countries have been examining how effective volunteers from the general public can be in supporting tree health surveillance. Our paper describes a project led by the Open Air Laboratories (OPAL) in the United Kingdom which tested the extent to which the public were motivated to participate in tree health surveillance. It also examined whether 'citizen scientists' could provide information which would be of genuine use to officials and scientists responsible for national tree health. The results suggest that there was considerable engagement from the public, who completed over 2800 surveys covering more than 4500 trees. Nevertheless, despite designing the OPAL survey specifically for untrained individuals, the results were only partially of value to tree health specialists. The paper discusses the results and concludes that involving citizens with some existing expert knowledge is probably the most effective way to generate more reliable data. Lay citizens can contribute effectively at critical times when additional surveillance capacity is needed, provided that suitable guidance and support are given. The incidence of tree disease has been increasing in the UK in recent years as a result of a range of alien tree pests and pathogens new to the country. In the early 2010s government staff resources to monitor, identify and eradicate these pathogens were limited, so we tested the efficacy of "citizen scientists" to support these needs. The Open Air Laboratories (OPAL) is a successful citizen science programme launched in 2007, which at that time of launch involved over 650 thousand people in a range of environmental surveys. In 2012–2013, the Food and Environment Research Agency (Fera) and Forest Research staff worked with OPAL and its partners to launch a citizen science tree health survey in Great Britain and this was extended to cover Northern Ireland until it closed in 2019. Over 2800 surveys were completed including records on more than 4500 trees, the majority from urban areas. This paper discusses the results of the survey and their value for the assessment of tree health. It also considers the implications of engagement with the general public for the future of tree health surveillance. Recommendations are made for further development of the OPAL "model" and more generally for the role of citizen science in this important area. [ABSTRACT FROM AUTHOR]

Oak processionary moth (Thaumetopoea processionea) or OPM was accidentally introduced into London on imported oak trees and now poses a threat to the future of oak in the urban landscape. Early attempts at eradication of the moth failed and significant resources have since been spent by government on monitoring and controlling OPM (through the use of insecticides or bio-pesticides) as it spreads into new areas. OPM is regulated in the UK to minimize risk of new introductions and reduce spread. Surveying for OPM and issuing of statutory notices for control is based on a geographical system of core, control and protected zones. While OPM will defoliate the trees leaving them vulnerable to other pests and diseases and stress factors, the caterpillars can also harm people and animals via tiny urticating hairs with the potential for dermatological or respiratory impacts. However, the biggest threat to the iconic British oak may be that the perceived risks associated with OPM, and costs of management may lead land managers to fell their oak trees, and not plant oak in the future. There is a need to better understand awareness, risk perceptions and decision-making around OPM management. We use a conceptual framework to explore decision-making and the trade-offs between the social, economic and ecological values associated with oak trees, and assessment of risk related to both the moth and control options. Twenty nine interviews were conducted in two London boroughs and across Greater London and in some surrounding counties covering a range of land types (e.g., parks, school grounds, amenity areas and private gardens) with infested or non-infested oak. We found a lack of evidence of human health impacts from OPM although land managers were concerned about public duty of care and potential reputational damage if they do not manage OPM. To address the challenges of dealing with OPM, land managers were taking a risk-based approach and managing OPM where it posed the highest potential risk to people. Respondents expressed strong emotional attachments to oak but it also has high biodiversity value which can lead to difficult decisions about management options. A risk-based approach moves beyond a 'one-size-fits-all' control method and focuses available resources where they are most needed and socially acceptable. An approach that allows for multiple values and perspectives on risk may provide a more sustainable long-term option for OPM management to ensure the future of oak in the city. [ABSTRACT FROM AUTHOR]

Ash dieback Hymenoscyphus fraxineus (T. Kowalski), is an alien fungal disease probably introduced to Europe from Asia that currently presents a significant threat to native ash (Fraxinus L. spp.). In the United Kingdom a large proportion of ash trees are found outside of woodlands. This means that a wide diversity of land owners and managers are stakeholders in the response to ash dieback. Local authorities (local government units) hold responsibility for managing ash trees along the highways and other public sites, with a focus on maintaining public health and safety. Developing local action plans (LAPs) for ash dieback is promoted by the government as way for local authorities to plan an effective strategic response at a landscape scale. However, risk assessment frameworks and the knowledge about ash dieback that is needed for quality decision-making at this level is still lacking. The scientific uncertainty around ash dieback progression, mortality rates, and the hazards presented by the trees at different stages of infection present knowledge problems. The research aims to (i) develop and evaluate an approach to addressing ash dieback suited to local authorities across the United Kingdom, and (ii) address the research gaps surrounding the local authority approaches to risk assessment and overcoming "knowledge problems." Our hypothesis is that action research can be used to develop an effective risk assessment framework and knowledge tools that can improve decision-making. Our research questions in support of these objectives are: (i) How do local authorities perceive, assess, and plan for risks? (ii) What information and knowledge do local authorities need to assess and manage the specific risks of ash dieback? Lastly, (iii) what processes drive the local authorities toward preparing and implementing LAPs? Data collection occurred between 2015–2019 and included: deliberative co-production and validation workshops, two survey questionnaires, and evaluative semi-structured interviews (SSIs). Local authorities were shown to assess risk and proportionality of response to ash dieback through processes of deliberative social learning mixing opinion, scientific and practice-based knowledge to reach a consensus over the methods and knowledge that would be used in decision-making. Placing ash dieback on corporate risk registers that cut across the multiple departments dealing with the problem facilitated political approval, action planning, and budget allocation. Generating locally specific knowledge and finding the resources and personnel to drive forward strategic planning and implementation were key to landscape scale responses and ratifying LAPs. Collaborative action research working on ways of assessing, learning, and responding to tree pests and diseases offer an important approach to problem-solving and developing responses at the landscape scale. [ABSTRACT FROM AUTHOR]

The challenges to forest health from climate change, globalization, contemporary trade practices and new recreational patterns require effective biosecurity. We asked: How is the biosecurity border for tree health understood and enacted by state and non-state actors? What are the consequences for tree health? Semi-structured interviews (N = 10) were conducted with scientists and other relevant actors (N = 21). The border was understood variously as: a biophysical boundary, often the coast; a geopolitical boundary, usually of the European Union; the points of main inspection focus; dispersed nodes of inspection; a 'pre-border' outside of UK; or by the location of detection activities. A wide range of state, non-state and hybrid groups are engaged in border practices. These practices have been altered due to trade and climate changes, are subject to cost and resource priorities and reflect particular knowledge flows and the biological nature of the agents. We suggest that there is an 'everyone' as well as 'everywhere' border that demands clarification of risks, roles and responsibilities, and we offer practical recommendations. We conclude that tree health border challenges are a manifestation of wider sustainability issues that enable us to explore human–nature relationships, democratic engagement and the pursuit of more sustainable futures. [ABSTRACT FROM AUTHOR]

The development of methods that can accurately detect physiological stress in forest trees caused by biotic or abiotic factors is vital for ensuring productive forest systems that can meet the demands of the Earth’s population. The emergence of new sensors and platforms presents opportunities to augment traditional practices by combining remotely-sensed data products to provide enhanced information on forest condition. We tested the sensitivity of multispectral imagery collected from time-series unmanned aerial vehicle (UAV) and satellite imagery to detect herbicide-induced stress in a carefully controlled experiment carried out in a mature Pinus radiata D. Don plantation. The results revealed that both data sources were sensitive to physiological stress in the study trees. The UAV data were more sensitive to changes at a finer spatial resolution and could detect stress down to the level of individual trees. The satellite data tested could only detect physiological stress in clusters of four or more trees. Resampling the UAV imagery to the same spatial resolution as the satellite imagery revealed that the differences in sensitivity were not solely the result of spatial resolution. Instead, vegetation indices suited to the sensor characteristics of each platform were required to optimise the detection of physiological stress from each data source. Our results define both the spatial detection threshold and the optimum vegetation indices required to implement monitoring of this forest type. A comparison between time-series datasets of different spectral indices showed that the two sensors are compatible and can be used to deliver an enhanced method for monitoring physiological stress in forest trees at various scales. We found that the higher resolution UAV imagery was more sensitive to fine-scale instances of herbicide induced physiological stress than the RapidEye imagery. Although less sensitive to smaller phenomena the satellite imagery was found to be very useful for observing trends in physiological stress over larger areas. [ABSTRACT FROM AUTHOR]