Hyperspectral remote sensing to detect biotic and abiotic stress in water hyacinth, (Eichhornia crassipes) (pontederiaceae)

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Doctor of Philosophy School of Animal, Plant and Environmental Sciences, Johannesburg, 2014Water hyacinth (Eichhornia crassipes) is one of the most notorious aquatic weeds in the world. Its management, despite the release of seven biocontrol agents since 1974, remains a problem in South Africa. This is often attributed to the high level of eutrophication. However, information on the effect of heavy metals or AMD on Neochetina eichhorniae and N. bruchi, which are the common and most widely established biocontrol agents in the country, is limited. In addition integrated management, which combines herbicides with biological control methods, is the current water hyacinth control method, and requires regular monitoring of the weed’s health status. This can be assessed via the canopy chlorophyll and water content, and can facilitate the decision when to intervene and what intervention measures are appropriate and timely. Hyperspectral Remote sensing (HRS) has the potential to be that monitoring tool. This thesis investigates the physiological status of water hyacinth grown with eight different heavy metals in a single-metal tub trial, three different simulated acid mine drainage (AMD) treatments in a pool trial under the influence of biocontrol agent from Neochetina spp., and in the Vaal River at the inlets of its tributaries, the Koekemoerspruit and the Schoonspruit. A hand-held spectrometer, the analytic spectral device (ASD), was used to measure reflectance. The hypothesis that HRS can detect the response of the plant to both the heavy metals and the biocontrol-induced stresses and their interactions was tested. Different spectral indices associated with the canopy chlorophyll and water content of water hyacinth were evaluated. Among these the modified normalized difference vegetation index (mNDVI) and those associated with the red edge position (the linear extrapolation and the maximum first derivative indices) were able to detect the metal, or AMD or weevil-induced plant health stresses and showed a strong positive correlation with the actual leaf chlorophyll content, measured by a SPAD-502 chlorophyll meter. Among the contaminants Cu, Hg, and Zn treatments from the single-metal tub trial and sulphate concentrations exceeding 700 mg/L in the AMD pool trial were detected by the RS as stressful to the plants. The RS also indicated that the water contamination level was greater downstream at the inlet of the Schoonspruit into the Vaal River, compared to the other sites after rainfall. These results were also consistent with actual measurements of the different plant growth parameters in all the trials and the weevils’ feeding and reproductive activities in the tub and pool trials. Thus, the results of this study indicated that the HRS has potential as a tool to assess the physiological status of water hyacinth from a remote position, which could be helpful in management of a serious national problem. The acquisition of spectral reflectance data at a larger scale, from aerial platforms, involves a complex data set with additional atmospheric interference that can mask the reflectance and which demands more complicated image analysis and interpretation. Thus, further such studies in future are recommended

Validity of realized vs. fundamental host range of insects used as biocontrol agents of invasive alien weeds: Eucalyptus weevil (Gonipterus scutellatus) as a test case

The conservative method of host specificity testing dictates that a potential biological control agent which shows polyphagous behaviour in the laboratory will be rejected, even though in a natural situation it may be monophagous or nearly so. To distinguish one from the other the performance of eucalyptus weevil, (Gonipterus scutellatus) was tested on 14 Eucalyptus and one Syzygium species in the laboratory, and the field. The weevil revealed different levels of polyphagy, depending on how the host plants were presented; as cut leaves, bouquets or sleeved-branches; or in choice or no-choice combinations. However, the fundamental host range was broader than the realized host range. Eucalyptus smithii and E. urophylla were the most preferred hosts (contrary to the literature), while E. saligna and Syzygium myrtifolia were immune to feeding and oviposition. Nevertheless, adult feeding and oviposition was more selective in the field, and the larvae are less discriminating than the adults. Finally, the weevil is shown to have a narrow host range within two sections of the subgenus Eucalyptus, sufficiently restricted if it was ever to be considered as a biocontrol agent

Exploring the Potential of Feature Selection Methods in the Classification of Urban Trees Using Field Spectroscopy Data

Mapping of vegetation at the species level using hyperspectral satellite data can be effective and accurate because of its high spectral and spatial resolutions that can detect detailed information of a target object. Its wide application, however, not only is restricted by its high cost and large data storage requirements, but its processing is also complicated by challenges of what is known as the Hughes effect. The Hughes effect is where classification accuracy decreases once the number of features or wavelengths passes a certain limit. This study aimed to explore the potential of feature selection methods in the classification of urban trees using field hyperspectral data. We identified the best feature selection method of key wavelengths that respond to the target urban tree species for effective and accurate classification. The study compared the effectiveness of Principal Component Analysis Discriminant Analysis (PCA-DA), Partial Least Squares Discriminant Analysis (PLS-DA) and Guided Regularized Random Forest (GRRF) in feature selection of the key wavelengths for classification of urban trees. The classification performance of Random Forest (RF) and Support Vector Machines (SVM) algorithms were also compared to determine the importance of the key wavelengths selected for the detection of the target urban trees. The feature selection methods managed to reduce the high dimensionality of the hyperspectral data. Both the PCA-DA and PLS-DA selected 10 wavelengths and the GRRF algorithm selected 13 wavelengths from the entire dataset (n = 1523). Most of the key wavelengths were from the short-wave infrared region (1300-2500 nm). SVM outperformed RF in classifying the key wavelengths selected by the feature selection methods. The SVM classifier produced overall accuracy values of 95.3%, 93.3% and 86% using the GRRF, PLS-DA and PCA-DA techniques, respectively, whereas those for the RF classifier were 88.7%, 72% and 56.8%, respectively

Pest categorisation of the Gonipterus scutellatus species complex

The Panelon Plant health performed a pest categorisation of the Australian Eucalyptus snout-beetle Gonipterusscutellatus (Coleoptera: Curculionidae), for the EU. G.scutellatus should be referred as the G.scutellatus species complex because it includes several cryptic species. A complete nomenclature of the species present in the EU is still pending. It is a quarantine pest listed in Annex IIB of Council Directive 2000/29/EC. Protected zones are in place in Greece and Portugal (Azores). In the EU, it has been found in Italy, France, Spain and Portugal. It only consumes Eucalyptus species leaves. The main pathways of spread are the trade of Eucalyptus timber, hitchhiking in various commodities, trade of apple fruit as well as of plants for planting or plant parts. Spread by flight is also possible. The climate of the EU protected zones is similar to that of the Member States (MS) where the G.scutellatus complex is established, and the pest's main host plants are present. The damaged trees suffer die-back and the development of epicormics shoots. Severe attacks may provoke massive amounts of tree death. Biological control by using the egg parasitoid wasp Anaphesnitens is the most effective control measure. Some species within the G.scutellatus complex are not yet present in the EU (including G.scutellatus sensu stricto) and might therefore be considered as potential union quarantine pests for the EU territory. At least two species within the G.scutellatus complex (most likely G.platensis and Gonipterus species no. 2) meet the criteria assessed by EFSA for consideration as potential protected zone quarantine pests for the territory of the protected zones: Greece and Portugal (Azores). The criteria for considering the G.scutellatus complex as a potential regulated non-quarantine pest for the EU are not met since plants for planting are not the main pathway

The capacity of aquatic macrophythes for phytoremediation and their disposal with specific reference to water hyacinth

The actual amount of fresh water readily accessible for use is <1 % of the total amount of water on earth, and is expected to shrink further due to the projected growth of the population by a third in 2050. Worse yet are the major issues of water pollution, including mining and industrial waste which account for the bulk of contamination sources. The use of aquatic macrophytes as a cost-effective and eco-friendly tool for phytoremediation is well documented. However, little is known about the fate of those plants after phytoremediation. This paper reviews the options for safe disposal of waste plant biomass after hytoremediation. Among the few mentioned in the literature are briquetting, incineration and biogasification. The economic viability of such processes and the safety of their economic products for domestic use are however, not yet established. Over half of the nations in the world are involved in mining of precious metals, and tailings dams are the widespread legacy of such activities. Thus, the disposal of polluted plant biomass onto mine storage facilities such as tailing dams could be an interim solution. There, the material can act as mulch for the establishment of stabilizing vegetation and suppress dust. Plant decomposition might liberate its contaminants, but in a site where containment is a priority

Mexican poppy (Argemone mexicana) control in cornfield using deep learning neural networks: a perspective

Mexican poppy (Argemone mexicana) is a widespread noxious annual weed associated with crops such as corn (Zea mays L.), and this weed is persistent because it produces a seed bank. This invasive weed species must be controlled even in the dry season because Mexican poppy has a deep-reaching root system, which taps water from deep soil layers. Cases of a human death caused by Mexican poppy seeds in South Africa, India, and other Eastern countries were reported from the early years of the twentieth century. However, when weeds are controlled uniformly instead of site-specific or precision farming method across the spatially variable fields, there are environmental pollution challenges. Site-specific weed control techniques have gained interest in the precision farming community over the last years mainly because of Global Positioning System (GPS) applications, and a controlled measure of herbicides are applied where there are weeds in the field, and areas with more clusters of weeds receive the correct amount of herbicide application. Mexican poppy has prickles and is a nuisance to farmers, and herbicides represent a severe health hazard to humans due to chemical concentrations in water. For that reason, we propose the design of a site-specific weed control plan to use a row-guided robot to detect and identify weeds with accuracy, control speed timeously, and spray herbicides with a high level of precision and automation. These robotics methods are reported to be environmentally conscious, and economically efficient with less labour and management. The proposed method of deep learning neural networks, which use row-guided robots, a machine is trained on multiple images to identify weeds automatically from the main crop, and release a controlled measure of herbicides based on weed location and density, and spray weeds on-the-go upon emergence

Distribution and abundance of invasive Tamarix genotypes in South Africa.

The exotic Tamarix chinensis and T. ramosissima, believed to have been introduced into South Africa in the early 1900s to control erosion on mine dumps, are invading riparian zones and have been proven to hybridise with T. usneoides, which is native to southern Africa. In this study, we document the abundance of invasive Tamarix genotypes in South Africa. Eleven riparian zones from the Northern, Eastern and Western Cape Provinces were surveyed. Three quadrats of 600 m2 each were selected per site. Plant density, canopy cover and tree height were recorded to quantify invasiveness. Leaf samples were randomly collected from an average of eight individuals per site to record genotypes of the invaders. Tamarix density and canopy cover were significantly greater than those of co-occurring trees and shrubs in Olifants River in De Rust (Western Cape Province). A linear correlation between percentage Tamarix spp. cover and other co-occurring tree and shrub species showed a strong negative relationship (R2 = 0.78). Genetic analysis showed that the Western and Eastern Cape Provinces have the highest proportion of the exotic Tamarix species and their hybrids. This suggests that these two provinces require urgent management intervention to contain the spread of the weed. The distinctions made between the native and the exotic Tamarix species and their hybrids should also facilitate the testing and future release of potential biological control agents

The Impact of Exotic Tamarix Species on Riparian Plant Biodiversity

This study investigated the impact of exotic Tamarix species on vascular plant biodiversity in riparian ecosystems in the Western Cape Province, South Africa. Vegetation was sampled, using 5 m wide belt transects, along the Leeu, Swart, and Olifants riparian areas, which had varying invasion intensities. Each transect was split into three zones (Zone 1: 0&ndash;15 m; Zone 2: 15&ndash;35, and Zone 3: &gt;35 m), which were identified at each site based on species composition across each riparian zone. Woody plant species were identified, counted, and their heights measured within the transects that were laid out from the waterpoint (Zone 1) outwards (Zone 2 and 3). Herbaceous aerial cover (HAC) was determined subjectively and objectified using the Walker aerial cover scale. Leeu River had the highest species richness (Dmg = 2.79), diversity (H&prime; = 2.17; &minus;ln&lambda; = 1.91; N1 = 8.76 and &alpha; = 4.13), and evenness (J&prime;= 0.80). The Swart River had the lowest species richness, which declined from Dmg = 1.96 (Zone 1) to Dmg = 1.82 (Zone 3). Exotic Tamarix species ranked in the top three most abundant woody vascular plant species along the Swart and Olifants rivers, where they ranked first and third, respectively. The Jaccard&rsquo;s and Sorenson&rsquo;s coefficients of similarity indicated that species differed greatly between the different sites, x&macr; &lt; 27% for both indices. The indices also indicated that the Swart River had the lowest level of species distinctness between zones (x&macr; &gt; 80%) while the Leeu River had the highest level of species distinctness (x&macr; &lt; 50%) between the different zones. These findings suggest a possible displacement of herbaceous and woody tree species by exotic Tamarix invasion, inter alia, a decrease in ecosystem functions and services associated with the loss in biodiversity, as well as significant bearings on the agricultural ecosystem by reducing the faunal diversity such as crop pollinators, inter alia

A rapid and accurate method of mapping invasive Tamarix genotypes using Sentinel-2 images

Background The management of invasive Tamarix genotypes depends on reliable and accurate information of their extent and distribution. This study investigated the utility of the multispectral Sentinel-2 imageries to map infestations of the invasive Tamarix along three riparian ecosystems in the Western Cape Province of South Africa. Methods The Sentinel-2 image was acquired from the GloVis website (http://glovis.usgs.gov/). Random forest (RF) and support vector machine (SVM) algorithms were used to classify and estimate the spatial distribution of invasive Tamarix genotypes and other land-cover types in three riparian zones viz. the Leeu, Swart and Olifants rivers. A total of 888 reference points comprising of actual 86 GPS points and additional 802 points digitized using the Google Earth Pro free software were used to ground-truth the Sentinel-2 image classification. Results The results showed the random forest classification produced an overall accuracy of 87.83% (with kappa value of 0.85), while SVM achieved an overall accuracy of 86.31% with kappa value of 0.83. The classification results revealed that the Tamarix invasion was more rampant along the Olifants River near De Rust with a spatial distribution of 913.39 and 857.74 ha based on the RF and SVM classifiers, respectively followed by the Swart River with Tamarix coverage of 420.06 ha and 715.46 hectares, respectively. The smallest extent of Tamarix invasion with only 113.52 and 74.27 hectares for SVM and RF, respectively was found in the Leeu River. Considering the overall accuracy of 85% as the lowest benchmark for a robust classification, the results obtained in this study suggests that the SVM and RF classification of the Sentinel-2 imageries were effective and suitable to map invasive Tamarix genotypes and discriminate them from other land-cover types