Loss Of Trees Research Articles

Historical expansion of tea plantations over 150years (1876-2023) in North Bengal, India.

The Camellia sinensis (L.) Kuntze agroforestry system has been a dominant driver of land transformation for over a century. However, most previous studies have not captured the dynamics of tea plantations since their inception. To address this research gap, this study investigates 150years (1876 to 2023) of tea area dynamics and two decades (2001-2022) of tree loss in the Bengal-Dooars region (Jalpaiguri and Alipurduar districts). Various data sources were employed, including Sentinel-2A imagery (10m), early twentieth century topographic maps at a 1:50,000 scale, and historical records from the British colonial period. Results revealed that the tea area expanded from 331 to 95,800ha (a 70% increase) during the study period. The 1-km grid-wise spatial analysis indicated that approximately 70% of the increase was attributed to the 60-90% and > 90% grid categories, signifying the expansion of large tea estates. Most tea gardens(TG) are sustained with trees, which can significantly contribute to carbon stock. Tree loss within and outside TG for 2001-2022 was analyzed using annual tree loss data at 30m from the Global Forest Watch (GFW) platform. Between 2001 and 2022, about 52.7% of tree loss was attributed to TG, although tea covers only 15.3% of the geographic area of the study region. Our findings highlight the historical expansion of tea plantations and their impact on natural land cover. We suggest that future studies address the mean age of TG along with tree fractions for improved carbon estimates.

Artificial tree microhabitats: Wound depth and position affect saproxylic beetles attracted to freshly veteranised trees

Abstract Veteran and ancient trees are key structures sustaining biodiversity in wooded landscapes. Their value depends on tree‐related microhabitats (TreMs) such as hollows, cracks and other structures related to wounds and wood decay. Decline and loss of veteran trees results in the loss of TreMs thus threatening the biodiversity associated with them. Veteranisation, that is, interventions aimed at creating or accelerating formation of rare TreMs in live trees, are thus increasingly applied to bridge gaps in habitat continuity and sustain the biodiversity associated with veteran trees. Several studies investigated the use of artificially created TreMs by various organisms. No study has, however, investigated saproxylic beetles attracted to freshly veteranised trees, and how different veteranisation techniques affect attractivity of veteranised trees to saproxylic beetles. We veteranised 48 sessile oaks using two types of deep and two types of shallow cuts and trapped saproxylic beetles on the veteranised and control trees in the first season after the intervention. The sampling yielded 280 species (6171 individuals) of saproxylic beetles, including 64 that are threatened. Veteranised trees attracted more abundant and diverse communities than control trees. Community composition differed between shallow and deep cuts and between the two types of deep cuts. Freshly veteranised trees thus attract diverse and abundant communities of saproxylic beetles consisting mainly of species potentially exploiting the wounds. The high proportion of threatened species, often associated with old oaks, suggests that veteranised trees benefit even some threatened saproxylic biodiversity already during the first year after the veteranisation.

Innovative strategies for characterizing and managing huanglongbing in citrus.

Huanglongbing is a severe citrus disease that causes significant tree and crop losses worldwide. It is caused by three Candidatus liberibacter species and spread by psyllids and infected budwood. Various methods have been used to diagnose and understand HLB, including recent advances in molecular and biochemical assays that explore the pathogen's mode of action and its impact on the host plant. Characterization is essential for developing sustainable HLB management strategies. Nanotechnology, particularly nano sensors and metal nanoparticles, shows potential for precise disease diagnosis and control. Additionally, antibiotics, nanomaterials, and genetic engineering techniques like transgenesis offer promising avenues for mitigating HLB. These diverse approaches, from conventional to cutting-edge, contribute to developing integrated HLB management strategies for sustainable citrus cultivation. The review highlights the significant advancements in conventional and advanced molecular and biochemical characterization of HLB, aiding in early detection and understanding of the infection mechanism. It emphasizes the multidimensional efforts required to characterize disease and devise innovative management strategies. As the citrus industry faces unprecedented challenges, exploring new frontiers in HLB research provides hope for sustainable solutions and a resilient future for global citrus cultivation.

Bat box monitoring: comparing multiple contemporary methods

ABSTRACT Bat boxes can be employed to provide mitigation for the loss of trees with bat roost potential. Eighty bat boxes were deployed by the Hamilton City Council as part of the bat mitigation strategy for the Southern Links Project in southern Hamilton. Several contemporary methods were employed to determine bat box occupancy to ensure effective monitoring. This included visual scoring assessments (e.g. staining, wetness), endoscope surveys, thermal imaging, and eDNA. Emergence survey data were provided by the University of Waikato which provided further insight into the accuracy of the methods. Jointly the methods confirmed the use of 34 Kent style boxes (n = 70; 49%). Indicating a high success rate of box utilisation over a relatively short period (two years). Of the methods, eDNA confirmed the largest percentage of bat box use. Comparatively, thermal imaging provided an alternative and less intrusive means of surveying on-the-day bat presence. However, there were instances where survey conditions (e.g. terrain, vegetation clutter, solar irradiance, rainfall) influenced the reliability of thermal imaging. While visual assessment and thermal imaging cannot be solely relied on, they provide a supportive tool for other monitoring techniques. They can help guide the application of more definitive methods such as eDNA.

Direct and Remote Sensing Monitoring of Plant Salinity Stress in a Coastal Back-Barrier Environment: Mediterranean Pine Forest Stress and Mortality as a Case Study

The increase in atmospheric and soil temperatures in recent decades has led to unfavorable conditions for plants in many Mediterranean coastal environments. A typical example can be found along the coast of the Campania region in Italy, within the “Volturno Licola Falciano Natural Reserve”, where a pine forest suffered a dramatic loss of trees in 2021. New pines were planted in 2023 to replace the dead ones, with a larger tree layout and interspersed with Mediterranean bushes to replace the dead pine forest. A direct (in situ) monitoring program was planned to analyze the determinants of the pine salinity stress, coupled with Sentinel-2 L2A data; in particular, multispectral indices NDVI and NDMI were provided by the EU Copernicus service for plant status and water stress level information. Both the vadose zone and shallow groundwater were monitored with continuous logging probes. Vadose zone monitoring indicated that salinity peaked at a 30 cm soil depth, with values up to 1.9 g/L. These harsh conditions, combined with air temperatures reaching peaks of more than 40 °C, created severe difficulties for pine growth. The results of the shallow groundwater monitoring showed that the groundwater salinity was low (0.35–0.4 g/L) near the shoreline since the dune environment allowed rapid rainwater infiltration, preventing seawater intrusion. Meanwhile, salinity increased inland, reaching a peak at the end of the summer, with values up to 2.8 g/L. In November 2023, salts from storm-borne aerosols (“sea spray”) deposited on the soil caused the sea-facing portion of the newly planted pines to dry out. Differently, the pioneer vegetation of the Mediterranean dunes, directly facing the sea, was not affected by the massive deposition of sea spray. The NDMI and NDVI data were useful in distinguishing the old pine trees suffering from increasing stress and final death but were not accurate in detecting the stress conditions of newly planted, still rather short pine trees because their spectral reflectance largely interfered with the adjacent shrub growth. The proposed coupling of direct and remote sensing monitoring was successful and could be applied to detect the main drivers of plant stress in many other Mediterranean coastal environments.

Estimated economic impact of fire blight on long-term orchard economic performance with susceptible and resistant rootstocks

We estimated the economic impact of theoretical fire blight induced tree loss using data from two long-term field trials in NY State. An economic analysis of profitability using Net Present Value (NPV) was conducted with three cultivars, eleven rootstocks and four planting systems. The impact of fire blight was modeled in terms of both the severity of the disease and the year of infection. We considered a range of scenarios with different infection rates (10 %, 50 %, 80 % and 100 %) of all the trees planted and different timings when the infection took place including the 1st year (prior to production), 5th year, 10th year and the 15th year during the life cycle of an orchard. The analysis showed that the smallest impact of fire blight induced losses on lifetime NPV occurred when the fire blight infection and tree death occurred in year 1 and was greatest when infection and tree death occurred in year 10. If the infection occurred in year 15 then the losses in NPV were less. As expected, the analysis showed that a low percentage of tree loss due to fire blight at any given year of the orchard life resulted in a low impact on lifetime NPV while greater levels of infection and tree loss were associated with higher losses in NPV. The use of fire blight resistant rootstocks dramatically reduced the negative impact of fire blight induced tree losses on NPV. With susceptible rootstocks (M.9 and M.26), the reduction in NPV with high levels of tree infection was as high as 70 % which would render the planting unprofitable, while with resistant rootstocks the losses in NPV were lower (<30 %) and the orchard would still be profitable. High-density orchard systems like the Tall Spindle system had less sensitivity to fire blight induced losses than lower density systems. Cultivar also had an important effect on the level of fire blight induced losses of NPV. With a high priced cultivar like ‘Honeycrisp’ the percentage loss in NPV was less than with the lower priced cultivars like ‘Fuji’ and ‘Gala’.

Public safety considerations constraint the conservation of large old trees and their crucial ecological heritage in urban green spaces

Large old trees in urban public green spaces deliver a diversity of values essential for human well-being, including biodiversity conservation. Yet, the conservation of large old trees bearing key wildlife microhabitats interferes with safety considerations. This intuitive notion, however, is backed by an insufficient and scattered body of evidence. Here, we empirically examined this process using data on 5974 trees across 510 sample plots, organized as quintuplets within 102 sample sites, including urban parks, cemeteries, recreational forests, and historic reserves in the urban agglomeration of Kraków, Poland. Our analyses demonstrate that trees situated in areas frequently visited by people, or those near walking paths, benches, or playgrounds, have elevated accident hazards and, therefore, necessitate intensive tree surgeries (pruning and logging) to remain harmless. Large old trees, which bear the most diverse microhabitats and pose greater risks when they collapse, are especially affected by these measures. Accordingly, we found that the co-occurrence of large trees with elevated accident hazards results in significant losses of dead and sloped trees, and trees with cavities, injuries, crown deadwood, fungal fruiting bodies, or epiphytes, particularly in parks and, to a lesser extent, in recreational forests. Apparently, some tree-related microhabitats, such as injuries, cavities, and microsoils, also emerge in risky spots after pruning. Our findings underscore that the conservation of large old trees and their ecological functions faces significant challenges due to safety considerations. To address conservation challenges and harmonize human coexistence with biodiversity, we recommend enhancing environmental awareness and reevaluating arboricultural and planning policies. This would involve establishing strategic and pocket reserves on city peripheries and interiors, allowing larger older trees to thrive and develop important microhabitats without compromising public safety. Otherwise, we risk losing many large old trees and/or their superior value for wildlife, which will regenerate over decades, if not centuries.

Fire Identification Based on Novel Dense Generative Adversarial Networks

Increasing death rates, damage to properties, and loss of trees can be caused by fires. In Australia and the United States of America, many fire incidents are reported annually. Due to that, both governments struggle from the devastation beyond plants, buildings, and infrastructure. A lot of people have lost their properties and land. Various innovations in fire detection technologies have been implemented to minimize the impacts of fires on the economy and lives. Some of these solutions are costly, while others lack accuracy. In this article, a novel deep-learning model to detect fires is presented. This model is based on new Novel Dense Generative Adversarial Networks (NDGANs) and image preprocessing technologies for fire detection through a continuous monitoring system. This system produces alarms if a fire or smoke is detected. The proposed approach was trained and tested on five datasets. This system was evaluated using four performance quantities, which are accuracy, sensitivity, dice, and F-score, and attained 98.87%, 97.64%, 98.82%, and 98.69% for the considered quantities, respectively. In addition, the proposed method was compared with other developed approaches and outperformed these methods. The presented New Dense Generative Adversarial Networks technology is useful in fire detection as shown from the conducted simulation experiments on MATLAB.

Rainfall, peak river flow and flow variability drive spatio‐temporal change in the extent of riparian woodland in an African protected area savanna

AbstractVerbal accounts, supported by limited ground‐based and satellite images, reveal decreasing riparian woodland and a loss of large trees along the rivers of the Kruger National Park (KNP, South Africa) over the last century. A multi‐decadal analysis was conducted to identify trends in extent and possible drivers of riparian woodland change. Aerial and satellite imagery (1936–2018) were used to quantify changes in the extent of riparian woodland at 18 sites on 14 rivers in KNP. These changes were compared in a multivariate time‐series with river flow and local rainfall. Particular attention was paid to cumulative flow effects, as well as the frequency and magnitude of large infrequent disturbances such as droughts and floods. Riparian tree cover fluctuated over the time period, and the trajectory of change varied between sites. Most (11) sites experienced a decrease in overall riparian tree cover over ~80 years, with these declines being significant at six sites. Peak flow and maximum rainfall events were strongly associated with these decreases, indicating that flood events are potentially the biggest driver of tree loss from the system. Indeed, the mega‐flood event of 2000 and subsequent large floods have resulted in substantial declines in riparian woodland extent in recent decades. Alternatively, flow variability and cumulative rainfall significantly influenced woodland expansion in isolated cases. With global change models predicting more erratic rainfall and an increased likelihood of large infrequent disturbances, together with increasing demands to abstract more water, the long‐term future of these dynamic habitats and their associated biota here is uncertain.

Resilient trees for urban environments: The importance of intraspecific variation

Societal Impact StatementTrees in urban environments provide us with shade, heat mitigation, flood abatement, noise and pollution reduction, pollination, beauty, and much more. However, many of these benefits are strongly connected to tree size and vitality, with larger, healthier trees providing ecosystem services more effectively, which means that selecting the right tree for site and function is crucial in order to gain all benefits from our urban trees.SummaryTrees play a major role in the Earth's biogeochemical processes, influencing soil production, hydrological, nutrient and carbon cycles, and the global climate. They store about 50% of the world's terrestrial carbon stocks, and provide habitats for a wide range of other species, supporting at least half of the Earth's known terrestrial plants and animals. Trees are not only found in forests and other natural ecosystems, but also in urban environments. Most of the human population is concentrated in cities, towns and villages, so urban trees are critical to meet on‐going and future social, economic and environmental challenges. However, many urban tree populations are strongly challenged by a changing climate, outbreaks of pests and pathogens and an urban development with increasingly dense cities and a high proportion of impermeable surface materials. The importance of intraspecific variation needs to be better acknowledged in this context, since poor matching of trees and the local climate and growing conditions can lead to extensive loss of valuable trees. By using the right genetic plant material for the challenging urban environments, a more resilient tree population with a greater diversity and higher capacity for delivering ecosystem services can be gained. Here, we wish to discuss the need to consider intraspecific variation when planning resilient tree populations for urban environments and how seed banks and botanical garden play important roles in efforts to improve the matching of genetic plant material for future environmental challenges. Strategies to enrich urban tree diversity and increase resilience are outlined.

Using a Cultural Keystone Species in Participatory Monitoring of Fire Management in Indigenous Lands in the Brazilian Savanna

There is a consensus that fire should be actively managed in tropical savannas to decrease wildfire risks, firefighting costs, and social conflicts as well as to promote ecosystem conservation. Selection and participatory monitoring of the effects of fire on cultural keystone species may be an efficient way to involve local stakeholders and inform management decisions. In this study, we investigated the effects of different fire regimes on a cultural keystone species in Central Brazil. With the support of diverse multiethnic groups of local fire brigades, we sampled Hancornia speciosa (Apocynaceae) populations across a vast regional range of 18 traditional territories (Indigenous Lands and Quilombola Territories) as well as four restricted Protected Areas. We considered areas under wildfires (WF), prescribed burns (PB) and fire exclusion (FE) and quantified tree mortality, canopy damage, loss of reproductive structures and fruit production following a simplified field protocol. Areas with H. speciosa populations were identified and classified according to their fire history, and in each sampled area, adult plants were evaluated. We hypothesized that WF would have larger negative impact on the population parameters measured, while FE would increase plant survival and fruit production. We found that tree mortality, canopy damage, and loss of reproductive structures were higher in areas affected by wildfires, which also had the lowest fruit production per plant compared to PB and FE areas, corroborating our hypotheses. However, we also found higher mortality in FE areas compared to PB ones, probably due to plant diseases in areas with longer FE. Considering these results and that the attempts to exclude fire from fire-prone ecosystems commonly lead to periodic wildfires, we argue that the Integrated Fire Management program in course in federal Protected Areas in Brazil—based on early dry season prescribed fires—is a good management option for this, and likely other, cultural keystone species in the Brazilian savanna.

Future (2020–2099) Carbon and Water Dynamics of Lehigh Valley Based on Land Use and Land Cover Change

Increased urbanization has reduced the amount of green space, resulting in a reduced carbon sink potential across urban landscapes. Through the use of biogeochemical modeling, different land use scenarios have been developed and run for the future (2020–2099) to compare and quantify the potential for change in carbon and water dynamics by having more tree cover and reducing impervious surfaces or turf lawns in Lehigh Valley, PA. These results show that the effect of deforestation is larger than the effect of reforestation. Due to young-stand age trees having a lower capacity for carbon storage than mature trees, the loss of the mature trees has a more immediate impact. The conversion of lawns or impervious surfaces to forests has somewhat similar effects, although the higher nutrients of lawns allow the forest to grow better. However, replacing impervious surfaces with trees reduces runoff more. This study shows that within the city of Bethlehem, the most socially vulnerable area benefits the most from increasing the number of trees. When converting 25% of the impervious area to forest, South Bethlehem significantly increased its vegetation carbon, productivity, and carbon storage, reduced its runoff, and generally created a safer and cleaner environment for residents.

Coevolutionary analysis of Pseudomonas syringae-phage interactions to help with rational design of phage treatments.

Treating plant bacterial diseases is notoriously difficult because of the lack of available antimicrobials. Pseudomonas syringae pathovar syringae (Pss) is a major pathogen of cherry (Prunus avium) causing bacterial canker of the stem, leaf and fruit, impacting productivity and leading to a loss of trees. In an attempt to find a treatment for this disease, naturally occurring bacteriophage (phage) that specifically target Pss is being investigated as a biocontrol strategy. However, before using them as a biocontrol treatment, it is important to both understand their efficacy in reducing the bacterial population and determine if the bacterial pathogens can evolve resistance to evade phage infection. To investigate this, killing curve assays of five MR phages targeting Pss showed that phage resistance rapidly emerges invitro, even when using a cocktail of the five phages together. To gain insight to the changes occurring, Pss colonies were collected three times during a 66-h killing curve assay and separately, Pss and phage were also coevolved over 10 generations, enabling the measurement of genomic and fitness changes in bacterial populations. Pss evolved resistance to phages through modifications in lipopolysaccharide (LPS) synthesis pathways. Bacterial fitness (growth) and virulence were affected in only a few mutants. Deletion of LPS-associated genes suggested that LPS was the main target receptor for all five MR phages. Later generations of coevolved phages from the coevolution experiment were more potent at reducing the bacterial density and when used with wild-type phages could reduce the emergence of phage-resistant mutants. This study shows that understanding the genetic mechanisms of bacterial pathogen resistance to phages is important for helping to design a more effective approach to kill the bacteria while minimizing the opportunity for phage resistance to manifest.

Enhancing Plant Disease Recognition on Mobile Devices: A Hybrid Approach with CNNs, Rule-Based Systems, and Machine Learning

The food industry has significantly boosted the agricultural economy of India, historically known as the largest producing nation with a strong agricultural identity. The primary crops include grains, fruits (such as potatoes, oranges, tomatoes), sugarcane, and specially cultivated grains and cotton. Maharashtra, a state in India, has experienced substantial economic growth, particularly attributed to citrus and cotton industries. This growth has generated employment opportunities and holds significant potential for the state's economic advancement. To sustain the prosperity of these industries, the government is actively addressing concerns related to disease control, Labor costs, and global market dynamics. In recent times, citrus canker, citrus greening, and black spots on cotton have emerged as severe threats to citrus crops in Maharashtra. Farmers are troubled by the costs associated with tree loss, scouting efforts, and the use of chemicals to control diseases. An automated detection system could play a crucial role in preventing and minimizing these losses, thereby safeguarding the industries, farmers, and the overall economy. This research focuses on developing disease detection through pattern recognition methods for various crops. The image detection process has some main categories which are image acquisition, image processing, and pattern recognition. Image preprocessing is used to process the image in a clear and clean format. Pattern recognition methods are then utilized to classify samples into different crop conditions. To assess classification approaches, results will be compared across different crops for disease detection. The goal is to demonstrate a classification accuracy surpassing existing models, reaching the highest. The research primarily aims to showcase the feasibility of disease detection based on visible symptoms on fruits or leaves. Data collection and initial knowledge acquisition are planned through offline and online approaches. The overall motive is to have accurate detection of the fruits and leaves thereafter using those results for diseases detection. Keywords: Machine Learning Algorithms, Plant disease detection, Image Recognition, Rule-Based mechanism, CNN, Detection technologies, Color Grading

Remote Sensing of Forests in Bavaria: A Review

In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests.

Bribe-Switching

The US Foreign Corrupt Practices Act (FCPA) prohibits the payment of bribes to foreign public officials. We uncover an unintended consequence—the shadow economies of the countries of these officials increase after FCPA enforcement. Our hypothesis is that corrupt officials may be switching to taking bribes from illegal markets. We find that one case of FCPA enforcement alone increases the shadow economy by as much as 0.27 percentage points (pp), tree loss—an indicator of illegal logging—by 0.027 pp, and trade misinvoicing by 0.5 pp. Our results suggest the need to harmonize anti-corruption policies across all sectors—legal and illegal.

Effects of Different Thinning Intensities on Carbon Storage in Pinus koraiensis Middle-Aged Plantations in Northeast China

Forest ecosystems are essential to the global carbon cycle because they are the biggest terrestrial carbon reserves. In the management of forests, thinning is a commonly employed strategy, impacting the respiration and biomass loss of trees, thereby modifying forest carbon dynamics. However, there is a lack of scientific research to confirm the impacts of thinning intensities on carbon storage in trees, soil layers, shrubs, and ground vegetation layers as well as its impact on wood production and growth rate. The goal of this study was to find the optimal thinning levels for increasing carbon sequestration during the growth stage of the Korean pine (Pinus koraiensis) middle-aged plantations in Northeast China. In this study, thinning intensity (0, 10, 11, 16, 18, and 22%) affected the carbon storage of trees, tree growth, volume, and, we suspected, soil layer, shrubs, and vegetation (herbs, litter, and grass) also. Specifically, after four years of thinning, the 18% treatment significantly increased total carbon storage, individual organ storage, growth, and tree volume (p &lt; 0.05). These results give us abundant information about how thinning affects the dynamics of carbon storage, wood production, and the interactions between soil and plants in P. koraiensis plantations, contributing to multi-objective management strategies for optimizing carbon sequestration, wood production, and ecosystem health.

Revolutionizing Plant Disease Detection: A Review of Deep Learning and Machine Learning Algorithms

The food industry has led the agricultural economy of the state all India to prosperity. India has historically been the largest producing nation having identity of Agricultural Land. Grains , fruits , Vegetables , such as potatoes, oranges, Tomato ,sugarcane and other specially grains and cottons are the chief crops of the India. Citrus and cotton industries have been a driving force behind Maharashtra's impressive economic growth.. The situation has created job opportunities for many people, boosting the state's economic potential. To maintain the prosperity of citrus and cotton industries, Government has been concerned about disease control, labour cost, and global market.&#x0D; During the recent past, citrus canker and citrus greening, Black spot-n cotton has become serious threats to citrus in Maharashtra. Infection by these diseases weakens trees, leading to decline, mortality, lower yields, and decreased commercial value. Likewise, the farmers are concerned about costs from tree loss, scouting, and chemicals used in an attempt to control the disease. An automated detection system may help in prevention and, thus reduce the serious loss to the industries, farmers and Economy of country.&#x0D; This research aims to the development of disease detection with pattern recognition approaches for these diseases in crop. The detection approach consists of three major sub-systems, namely, image acquisition, image processing and pattern recognition. The imaging processing sub-system includes image preprocessing for background noise removal, leaf boundary detection and image feature extraction. Pattern recognition approaches will be use to classify samples among several different conditions on crops.&#x0D; In order to evaluate the classification approaches, results will be compared between classification methods for the different induvial fruits, vegetable, grains disease detection. Obtained results will help in demonstration of classification accuracy which is targeted as better than existing for proposed model as high as 97.00%. This study aimed to assess the potential of identifying plant diseases by examining visible signs on fruits and leaves. These data collection and initial knowledge acquisition is plan in offline approaches. By implementing this simple model, we can achieve a more favourable cost-to-production ratio compared to complex solutions.

Demographic change and loss of big trees in resprouting eucalypt forests exposed to megadisturbance

AbstractAimIncreased tree mortality linked to droughts and fires is occurring across temperate regions globally. Vegetation recovery has been widely reported; however, less is known about how disturbance may alter forests structurally and functionally across environmental gradients. We examined whether dry forests growing on low‐fertility soils were more resilient to coupled extreme drought and severe fire owing to lower tree mortality rates, higher resprouting success and persistence of juveniles relative to wetter forests on more fertile soils.LocationFire‐tolerant eucalypt forests of temperate southeastern Australia.Time period2020–2023.Major taxa studiedEucalyptus, Corymbia, Angophora.MethodsDemographic surveys of tree mortality and regeneration in all combinations of dry/wet forest, fertile/less fertile substrates exposed to extreme drought and fire were conducted. We used Bayesian regression modelling to compare tree mortality, diameter, response traits, population structure and occurrence of fire scars between substrates/forest types.ResultsOverall mortality (20%–33%) and topkill (34%–41%) were within historically reported ranges for various forests and soil types. However, we observed an atypical trend of increased mortality and topkill in the largest trees, particularly when they had structural damage from past fires. Trees in wet forests on more fertile soils had the highest levels of mortality. Numbers of persistent resprouting juveniles were highest in dry forests on low‐fertility soils. Dry forests growing on low‐fertility soils appear more resilient to compound disturbances due to lower rates of mortality and higher rates of juvenile persistence. Wet forests on more fertile soils may experience greater demographic change due to higher mortality of small and large trees.Main conclusionsMesic forests on relatively fertile soils were found to be at relatively high risk of demographic change from compound disturbances. Combined, fire and drought are likely to reduce the number of large trees in affected areas, with consequences for forest carbon cycling and storage.

Urban density and the urban forest: How well are cities balancing them in the context of climate change?

Urban forests are gaining recognition as a nature-based solution to climate change and other social-environmental issues in cities. Yet, the integration of urban forests may conflict with other climate measures such as urban densification, which may create hostile growing conditions for trees and lead to tree decline or loss. While previous studies have identified conflicts between densification and urban forests, there is a lack of research mapping the relationships among climate action, urban planning, and urban forest policies. This study involved semi-structured interviews with 14 key informants in Metro Vancouver, Canada, a rapidly-densifying region.Twenty-six trade-offs and 24 synergies were identified in five areas/sectors, such as (re)development and infrastructure. While strategic policies often highlighted synergies, policy implementation processes and outcomes often encountered trade-offs due to factors such as limited budgets and low political priority. Notably, most trade-offs and synergies were found in the same areas - (re)development and infrastructure - and shared the same contributing factors, such as political priority of urban forestry, suggesting areas of opportunity to transform trade-offs into synergies through appropriate planning and monitoring. The study also highlighted the need for further research on the interactions and impacts among municipal policies for more effective implementation and outcomes.