Agricultural Robot for Intelligent Detection of Pyralidae Insects

The Pyralidae insects are one of the main pests in economic crops. However, the manual detection and identification of Pyralidae insects are labor intensive and inefficient, and subjective factors can influence recognition accuracy. To address these shortcomings, an insect monitoring robot and a new method to recognize the Pyralidae insects are presented in this chapter. Firstly, the robot gets images by performing a fixed action and detects whether there are Pyralidae insects in the images. The recognition method obtains the total probability image by using reverse mapping of histogram and multi-template images, and then image contour can be extracted quickly and accurately by using constraint Otsu. Finally, according to the Hu moment characters, perimeter, and area characters, the contours can be filtrated, and recognition results with triangle mark can be obtained. According to the recognition results, the speed of the robot car and mechanical arm can be adjusted adaptively. The theoretical analysis and experimental results show that the proposed scheme has high timeliness and high recognition accuracy in the natural planting scene

Using big data to understand evolutionary patterns in Geometridae and Erebidae, the two most diverse families of Lepidoptera

Lepidoptera (moths and butterflies) are one of the most diverse groups of organisms on earth. They have conquered all the continents apart from Antarctica. The reasons of such high diversity are still not clear. One of the first steps to study the causes of such evolutionary success is to have a clear idea of their phylogenetic relationships. In this thesis I focus on the diversity of two of the most diverse families of Lepidoptera, Geometridae with over 23,000 described species and Erebidae with over 24,000 species. In the case of Geometridae I focus in obtaining a robust phylogenetic hypothesis and then study the diversification dynamics and the biogeographical history which have shaped their actual diversity and distribution. In this project I used the most complete dataset of the family in order to study their evolutionary patterns. In the case of the Erebidae family, obtaining a robust phylogenetic hypothesis was more challenging. In the most complete study of the group up to date, using a multi locus Sanger based approach, it was not possible to resolve the deep phylogeny of the family. Therefore, I used high throughput sequencing (HTS) approaches to resolve the complex deep phylogenetic history of the group. In this project I used old DNA extracts of over 10 years old to explore the possibility of using this genetic resource for genomic studies. In addition, I evaluated the accuracy and range of resolution of the mitochondrial genomes in this family. And finally, I explored the alternative possibilities which the HTS approaches offer us to study the presence of symbiotic interactions using genomic data

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset

In an effort to catalog insect biodiversity, we propose a new large dataset of hand-labelled insect images, the BIOSCAN-Insect Dataset. Each record is taxonomically classified by an expert, and also has associated genetic information including raw nucleotide barcode sequences and assigned barcode index numbers, which are genetically-based proxies for species classification. This paper presents a curated million-image dataset, primarily to train computer-vision models capable of providing image-based taxonomic assessment, however, the dataset also presents compelling characteristics, the study of which would be of interest to the broader machine learning community. Driven by the biological nature inherent to the dataset, a characteristic long-tailed class-imbalance distribution is exhibited. Furthermore, taxonomic labelling is a hierarchical classification scheme, presenting a highly fine-grained classification problem at lower levels. Beyond spurring interest in biodiversity research within the machine learning community, progress on creating an image-based taxonomic classifier will also further the ultimate goal of all BIOSCAN research: to lay the foundation for a comprehensive survey of global biodiversity. This paper introduces the dataset and explores the classification task through the implementation and analysis of a baseline classifier

Thinking outside the graph: scholarly knowledge graph construction leveraging natural language processing

Despite improved digital access to scholarly knowledge in recent decades, scholarly communication remains exclusively document-based. The document-oriented workflows in science publication have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. In this form, scientific knowledge remains locked in representations that are inadequate for machine processing. As long as scholarly communication remains in this form, we cannot take advantage of all the advancements taking place in machine learning and natural language processing techniques. Such techniques would facilitate the transformation from pure text based into (semi-)structured semantic descriptions that are interlinked in a collection of big federated graphs. We are in dire need for a new age of semantically enabled infrastructure adept at storing, manipulating, and querying scholarly knowledge. Equally important is a suite of machine assistance tools designed to populate, curate, and explore the resulting scholarly knowledge graph. In this thesis, we address the issue of constructing a scholarly knowledge graph using natural language processing techniques. First, we tackle the issue of developing a scholarly knowledge graph for structured scholarly communication, that can be populated and constructed automatically. We co-design and co-implement the Open Research Knowledge Graph (ORKG), an infrastructure capable of modeling, storing, and automatically curating scholarly communications. Then, we propose a method to automatically extract information into knowledge graphs. With Plumber, we create a framework to dynamically compose open information extraction pipelines based on the input text. Such pipelines are composed from community-created information extraction components in an effort to consolidate individual research contributions under one umbrella. We further present MORTY as a more targeted approach that leverages automatic text summarization to create from the scholarly article's text structured summaries containing all required information. In contrast to the pipeline approach, MORTY only extracts the information it is instructed to, making it a more valuable tool for various curation and contribution use cases. Moreover, we study the problem of knowledge graph completion. exBERT is able to perform knowledge graph completion tasks such as relation and entity prediction tasks on scholarly knowledge graphs by means of textual triple classification. Lastly, we use the structured descriptions collected from manual and automated sources alike with a question answering approach that builds on the machine-actionable descriptions in the ORKG. We propose JarvisQA, a question answering interface operating on tabular views of scholarly knowledge graphs i.e., ORKG comparisons. JarvisQA is able to answer a variety of natural language questions, and retrieve complex answers on pre-selected sub-graphs. These contributions are key in the broader agenda of studying the feasibility of natural language processing methods on scholarly knowledge graphs, and lays the foundation of which methods can be used on which cases. Our work indicates what are the challenges and issues with automatically constructing scholarly knowledge graphs, and opens up future research directions

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.Ihmisen toiminnan seurauksena ympäristön tila on heikentynyt kiihtyvällä vauhdilla. Ilmasto lämpenee, metsähakkuut ja metsäpalot lisääntyvät ja luonnon monimuotoisuus on katoamassa. Ympäristöongelmia ja -uhkia voidaan tutkia ja mallintaa geoinformatiikan menetelmin ja metodein: kaukokartoituksen, paikkatietojärjestelmien (GIS) sekä spatiaalis-tilastollisten ennustemallien avulla. Väitöskirjassa tutkittiin geoinformatiikan menetelmin geospatiaalista aineistoa hyväksi käyttäen: (i) Täpläverkkoperhosen (Melitaea cinxia) esiintymistä Ahvenanmaalla; (ii) Lehtimittarin (Scopulini moths; Lepidoptera: Geometridae, Sterrhinae) esiintymisen spatiaalis-temporaalista levinneisyyttä ja diversiteettiä globaalissa mittakaavassa; (iii) alkuperäismetsien häviämistä ja (iv) asutuksen levinneisyyttä Taita Hills -ylänköalueella Keniassa, sekä (v ja vi) savannipalojen esiintymistä ja paloarpien laajuuden arviointia Itä-Kaprivilla, Namibiassa. Tulokset: (i) Ahvenanmaalla esiintyvälle Täpläverkkoperhoselle luotiin paikkatietokanta, jonka avulla selvitettiin lajin metapopulaation spatiaalis-temporaalisia tekijöitä. Tärkein tulos todisti että paikallisilmaston vaikutus on yksi merkittävimmistä tekijöistä Täpläverkkoperhosen populaatioiden koon vaihtelussa. (ii) Paikkatietomenetelmin pystyttiin selvittämään Lehtimittarin (Scopulini moths; Lepidoptera: Geometridae, Sterrhinae) globaali maantieteellinen levinneisyys ja diversiteetti. Lajia tavataan ympäri maailmaa paitsi arktisilla alueilla. Pääosa lajeista on löydetty troppisilta alueilta. Diversiteetti on erityisen runsasta Saharan eteläpuoleisessa Afrikassa. (iii) Taita Hills ylänköalueella alkuperäismetsät ovat vähentyneet 50% (260 hehtaaria) vuodesta 1955 vuoteen 2004. Kuitenkin metsäpinta-ala oli Taita Hillsin ylänköalueella pienentynyt vain 2% johtuen metsänistutuksista. Maankäytön muutostulkintaan perustuen Taita Hills ylänköalueen alkuperäismetsät ovat pääosin muuttuneet maatalousmaaksi. Alkuperäismetsien tilalle on myös istutettu ns. eksoottisia lajikkeita kuten eukalyptusta, joka on heikentänyt metsien laatua, jolla on haitalliset vaikutukset mm. eliölajien monimuotoisuuteen Taita Hillsin alueella. (iv) Taita Hills ylänköalueen asutuksen levinneisyyttä voidaan mallintaa geospatiaalisilla karttatasoilla ja spatiaalis-tilastollisilla ennustemenetelmillä. Tutkimuksessa ilmeni, että satelliittikuvalta saadut ensimmäisen asteen tilastolliset tekstuuripiirteet ja toisen asteen tilastolliset tekstuuripiirteet, jotka perustuvat ns. Haralickin tekstuuripiirteiden yhtenevyysmatriisiin, olivat parhaita muuttujia selittämään asutuksen levinneisyyttä. Tutkimus paljasti että asutuksen mallintamiseen ei välttämättä tarvita satelliittikuvalta luokiteltua maankäyttökarttatasoa, sillä ensimmäisen ja toisen asteen tilastolliset tekstuuripiirteet olivat parempia selittäviä muuttujia ennustemalleissa. (v) Itä-Kaprivilla spatiaalis-tilastollisella ennustemallilla; yleistetty lineaarinen regressio (generalized linear model, GLM) voidaan arvioida paloalueiden laajuus paikallistasolla tarkemmin kuin käyttämällä olemassa olevaa MODIS satelliittiin perustuvaa (MCD45A1) globaalia paloaluemallia. Spatiaalis-tilastollisissa malleissa on kuitenkin huomioitava palojen spatiaalinen autokorrelaatio kalibrointiprosessissa. (vi) Kahdeksaa eri spatiaalis-tilastollista ennustemallinnusmenetelmää verrattiin palojen esiintymisen ja paloalueiden laajuuden analyysissä Itä-Kaprivilla. GBM (Generalized boosting methods) -menetelmä osoittautui parhaaksi sekä palojen esiintymisen ja paloalueiden laajuuden mallintamisessa. Ennustemalleilla pystyttiin arvioimaan paloalueiden laajuus ja paloriskialueet tarkemmin kuin käyttämällä olemassa olevaa MODIS satelliittiin perustuvaa (MCD45A1) globaalia paloaluemallia

Writing Science Through Critical Thinking

Written and extensively class tested with NSF/NIH support, this timely and useful text addresses a crucial need which is acknowledged in most universities and colleges. It is the need for students to learn to write in the context of their field of study; in this case science. Although numerous how to writing books have been published, few, if any, address the central pedagogical issues underlying the process of learning to think and write scientifically. The direct connection between this writing skill and that of critical thinking is developed with engaging style by the author, an English professor. Moriarty\u27s book is an invaluable guide for both undergraduate and graduate science students. In the process of learning the specific requirements of organization demanded by scientific writing, students will develop strategies for thinking through their scientific research, well before they sit down to write. This instructive text will be useful to students who need to satisfy a science writing proficiency requirement in the context of a science course, a course in technical writing, advanced composition, or writing for the profession.https://digitalcommons.hollins.edu/facbooks/1047/thumbnail.jp

Evolution of associations between Cymothoe butterflies and their Rinorea host plants in tropical Africa

This thesis aimed to elucidate the evolutionary history of the associations between Cymothoeforest butterflies (Nymphalidae, Limenitidinae) and their Rinoreahost plants (Violaceae) in tropical Africa. Insects are by far the most diverse group of multicellular organisms on earth. Because most insect species are herbivores, understanding the evolution of interactions between herbivorous insects and their host plants is therefore crucial to comprehend global patterns in terrestrial biodiversity. The Cymothoe-Rinoreasystem is especially suitable for untangling processes shaping patterns of insect-host plant associations because of its high level of specificity (mostly monophagous) and the large number of related species involved (33 insect herbivores and 32 hosts). Obviously, any evolutionary study relies on a solid classification and taxonomy of the organisms under study. Unfortunately, however, in Cymothoeas well as Rinorea, taxonomy and classification is still partly unresolved. To improve taxonomy of Cymothoeand facilitate efficient identification of immature specimens found on Rinoreahost plants, we generated an extensive dataset of 1204 DNA barcode sequences (Chapter 2). Application of a novel taxonomic decision pipeline for integrating DNA barcodes with morphology and biogeography proved instrumental for solving taxonomic problems in Cymothoeand five taxa within Cymothoecould be confidently raised to species level. In addition, our DNA barcode data set allowed for the identification of 42 immature specimens from six different countries, significantly increasing the data on Cymothoehost plant associations. Nevertheless, our results also demonstrated that not all species of Cymothoecan be confidently delimited or identified. We hypothesize that this is probably due to incomplete lineage sorting and introgression (the latter possibly mediated through Wolbachiaendosymbionts) between recently diverged Cymothoespecies. In order to assess what are the best methods for matching DNA barcodes from recently diverged species, we compared six methods in their ability to correctly match DNA barcodes from selected published empirical data sets as well as simulated data (Chapter 3). Our results showed that, even though recently diverged species pose a significant problem for effective DNA barcoding, sensitive similarity-based and diagnostic methods can significantly improve identification performance compared with the commonly used tree-based methods. To improve classification and clarify the biogeographic history of Rinorea, we presented an updated phylogenetic tree of Rinoreawith increased taxonomic sampling, using plastid as well as nuclear DNA sequences (Chapter 5). Phylogenetic relationships inferred from nuclear DNA data were generally congruent with those based on evidence from plastid haplotypes from earlier studies of Rinoreaand helped resolve additional clades, some of which warrant further taxonomic study. Divergence time estimations indicated that Rinoreaoriginated in the Neotropics and reached Africa in the Eocene through trans-Atlantic dispersal. From Africa, Rinoreasubsequently dispersed into Asia in the Oligocene or early Miocene, and colonized Madagascar multiple times independently within a relatively recent time scale (Pliocene), suggesting that factors governing the independent colonizations of Rinoreato Madagascar may have been similar. In Chapter 4 we assessed whether differential rates of net species diversification in the African butterfly sister genera Harma(1 species) and Cymothoe(approximately 82 species) could best be explained by shifts to novel host plants (from Achariaceae to Rinorea) or by environmental factors such as changing climate. We generated the first time-calibrated species-level molecular phylogenetic tree of Harmaand Cymothoeand found that, after their divergence in the Miocene (15 Mya), net species diversification was low during the first 7 Myr. Coinciding with the onset of diversification of Cymothoein the late Miocene (around 7.5 Mya) there was a sharp and significant increase in diversification rate, suggesting a rapid radiation. This increased rate did not correlate with host plant transition from Achariaceae to Rinoreahost plants, but rather with a period of global cooling and desiccation, indicating that tropical forest fragmentation may well have driven the elevated diversification rates in Cymothoe. Finally, in Chapter 6 we integrated the time-calibrated phylogenetic evidence from Cymothoeand Rinoreapresented in chapters 4 and 5 with updated host association records from the field, with the aim to distinguish between alternative scenarios for the evolution of insect-host plant associations. Our results showed that: (i) divergences among extant Cymothoeare more recent than those among their associated Rinoreahosts, suggesting asynchronous diversification of Cymothoeherbivores onto already diversified clades within African Rinorea; (ii) phylogenetic trees of Cymothoeand their associated Rinoreahost plants are discordant and current associations between Cymothoeherbivores and their Rinoreahosts have developed primarily through a process of host shifting rather than by cospeciation; and (iii) related Cymothoetend to feed on related Rinoreahosts. Based on the available data, we propose a recent origin of Rinorea{}-feeding by Cymothoebutterflies with a single colonization of pre-existing lineages in the late Miocene. Current associations are best explained by a predominance of shifts among related plants, probably due to constraints in larval physiology and oviposition behaviour. Overall, these findings are in agreement with a growing body of substantial evidence to suggest that divergences of herbivorous insects and their host plants are asynchronous, and that evolutionary dynamics of hosts and parasites do not favour cospeciation. Insect-plant interactions are receiving increasing attention because of their importance in crop production and protection. At the same time, an increasing number of insects and plants that have evolved in separation are currently coming into contact due to human activities and climatic changes. It is therefore tempting to find implications of our findings for insect-host plant associations for agricultural systems (Chapter 7). Based on our results, one might predict that insects will only become pests of crops that are closely related to their natural host. Extrapolating our findings to an agricultural setting is difficult, however, because of the difference in selective pressures between natural and agricultural ecosystems.</p

Testing the utility of DNA barcoding on dipteria of eThekwini.

Master of Science in Genetics. University of KwaZulu-Natal. Durban, 2016.Abstract available in PDF file