Citizen Science and Geospatial Capacity Building

This book is a collection of the articles published the Special Issue of ISPRS International Journal of Geo-Information on “Citizen Science and Geospatial Capacity Building”. The articles cover a wide range of topics regarding the applications of citizen science from a geospatial technology perspective. Several applications show the importance of Citizen Science (CitSci) and volunteered geographic information (VGI) in various stages of geodata collection, processing, analysis and visualization; and for demonstrating the capabilities, which are covered in the book. Particular emphasis is given to various problems encountered in the CitSci and VGI projects with a geospatial aspect, such as platform, tool and interface design, ontology development, spatial analysis and data quality assessment. The book also points out the needs and future research directions in these subjects, such as; (a) data quality issues especially in the light of big data; (b) ontology studies for geospatial data suited for diverse user backgrounds, data integration, and sharing; (c) development of machine learning and artificial intelligence based online tools for pattern recognition and object identification using existing repositories of CitSci and VGI projects; and (d) open science and open data practices for increasing the efficiency, decreasing the redundancy, and acknowledgement of all stakeholders

Assessing the Benefits, Challenges and Scientific Value of Community Science Programs: A Case Study Using Bumble Bee Watch

We are experiencing a biodiversity crisis but resources to help species are limited. Scientists are turning to community science to complement traditional scientific methods. Bumble bees (Bombus spp.) are important pollinators in temperate regions, but many are in decline, and more information is needed to conserve them. The Bumble Bee Watch (BBW) program collects this through photos submitted by volunteers and identified by experts. Yet many community science programs struggle. Chapter 2 reviews common successes and challenges, offering best practices for developing and running programs. To determine whether BBW is filling knowledge gaps, Chapter 3 compares its data to the Bumble Bees of North America database (BBNA) over all years and 2010-2020. BBW recorded 41 species (BBNA had 48) from all parts of the continental US and Canada, confirmed persistence, and provided novel locations for species outside of and within the known extent of occurrence. BBW showed its greatest impact from 2010-2020 by contributing 25% of all records, 28% of all unique locations, and 32% new plant forage genera. BBW does not replace traditional surveys, but does complement them. Chapter 4 shows that B. pensylvanicus is critically endangered in Canada according to IUCN Red List criteria. BBW provided 20% of all B. pensylvanicus records and 36% of its sites over the 2007-2016 period assessed, and thus provided important information on its current abundance and distribution. No experience is required to participate in BBW, but having participants able to accurately identify species is beneficial. Chapter 5 explores the percent agreement and veracity of participant species identifications compared to experts, with the average being 53% and 56%, respectively. With better educational resources, participants may be better trained to identify species more accurately. Understanding the motivations and insights of community science participants is important. Chapter 6 discusses the results of a BBW user and expert survey: participants want to contribute to science and save the bees, and report an increase in knowledge and skills after participating. Although areas for improvement are noted, BBW is an important tool for Bombus researchers, and demonstrates the value that community science has for species conservation

Ecology and Conservation of Parrots in Their Native and Non-Native Ranges

This book focuses on parrots, which are among the most fascinating, attractive, and threatened birds, combining and synthesizing recent research on the biology, ecology, and conservation of both native and non-native parrot populations across the world

Integrating host population contact structure and pathogen whole-genome sequence data to understand the epidemiology of infectious diseases : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy, Massey University, Manawatū, New Zealand

With advances in high-throughput sequencing technologies, computational biology, and evolutionary modelling, pathogen sequence data is increasingly being used to inform infectious disease outbreak investigations; supporting inferences on the timing and directionality of transmission as well as providing insights into pathogen evolutionary dynamics and the development of antimicrobial resistance. This thesis focuses on the application of pathogen whole-genome sequence data in conjunction with social network analysis to investigate the transmission dynamics of two important pathogens; Campylobacter jejuni and Staphylococcus aureus. The first four studies centre around the recent emergence of an antimicrobial-resistant C. jejuni strain that was found to have rapidly spread throughout the New Zealand commercial poultry industry. All four studies build on the results of an industry survey that were not only used to determine the basic farm demographics and biosecurity practices of all poultry producers, but also to construct five contact networks representing the on- and off-farm movement patterns of goods and services. Contact networks were used in study one to investigate the relationship between farm-level contact risk pathways and the reported level of biosecurity. However, despite many farms having a number of contact risk pathways, no relationship was found due to the high level of variability in biosecurity practices between producers. In study two the contact risk between commercial poultry, backyard poultry, and wild birds was investigated by examining the spatial overlap between the commercial contact networks and (i) all poultry transactions made through the online auction website TradeMe® and, (ii) all wild bird observations made through the online citizen science bird monitoring project, eBird, with study results suggesting that the greatest risk is due to the growing number of online trades made over increasingly long distances and shorter timespans. Study three further uses the commercial contact networks to investigate the role of multiple transmission pathways on the genetic relatedness of 167 C. jejuni isolates sampled from across 30 commercial poultry farms. Permutational multivariate analysis of variance and distance-based linear models were used to explore the relative importance of network distances as potential determinants of the pairwise genetic relatedness between the C. jejuni isolates, with study results highlighting the importance of transporting feed vehicles in addition to the geographical proximity of farms and the parent company in the spread of disease. In the last of the four C. jejuni studies, a compartmental disease transmission model was developed to simulate both the spread and sequence mutations across an outbreak within the commercial poultry industry. Simulated sequences were used in an analysis mirroring the methods used in study three in order to validate the approaches examining the contribution of local contacts and network contacts towards disease transmission. An additional analysis is also performed in which the simulated sequence data is used to infer a transmission tree and explore the use of pathogen phylogenies in determining who-infected-whom across different model systems. A further study, motivated by the application of whole-genome sequence data to infer transmission, investigated the spread of S. aureus within the New Zealand dairy industry. This study demonstrated how whole-genome sequence data can be used to investigate pathogen population and evolutionary dynamics at multiple scales: from local to national and international. For this study, the genetic relatedness between 57 bovine-derived S. aureus isolates sampled from across 17 New Zealand dairy herds were compared with 59 S. aureus isolates that had been previously sampled and characterised from humans and domestic pets from across New Zealand and 103 S. aureus isolates extracted from GenBank that included both human and livestock isolates sampled from across 19 countries. Results from this study not only support evidence showing that the movement of live animals is an important risk factor for the spread of S. aureus, but also show that using cattle-tracing data alone may not be enough to fully capture the between farm transmission dynamics of S. aureus. Overall, by using these two pathogen examples, this thesis demonstrates the potential use of pathogen whole-genome sequence data alongside contact network data in an epidemiological investigation, whilst highlighting the limitations and future challenges that must be considered in order to continue to develop robust methods that can be used to reliably infer the transmission and evolutionary dynamics across a range of infectious diseases

Finding What You Need: A Guide to Citizen Science Guidelines

In line with the growth in citizen science projects and participants, there are an increasing number of guidelines on different aspects of citizen science (e.g. specific concepts and methodologies; data management; and project implementation) pitched at different levels of experience and expertise. However, it is not always easy for practitioners to know which is the most suitable guideline for their needs. This chapter presents a general classification of guidelines, illustrating and analysing examples of each type. Drawing on the EU-Citizen.Science project, we outline criteria for categorising guidelines to enable users to find the right one and to ensure that guidelines reach their intended audience. We discuss challenges and weaknesses around the use and creation of guidelines and, as a practical conclusion, provide a set of recommendations to consider when creating guidelines

Data Quality in Citizen Science

This chapter discusses the broad and complex topic of data quality in citizen science – a contested arena because different projects and stakeholders aspire to different levels of data accuracy. In this chapter, we consider how we ensure the validity and reliability of data generated by citizen scientists and citizen science projects. We show that this is an essential methodological question that has emerged within a highly contested field in recent years. Data quality means different things to different stakeholders. This is no surprise as quality is always a broad spectrum, and nearly 200 terms are in use to describe it, regardless of the approach. We seek to deliver a high-level overview of the main themes and issues in data quality in citizen science, mechanisms to ensure and improve quality, and some conclusions on best practice and ways forwards. We encourage citizen science projects to share insights on their data practice failures. Finally, we show how data quality assurance gives credibility, reputation, and sustainability to citizen science projects

Developing tools for improved population and range estimation in support of extinction risk assessments for Neotropical birds

Species abundance and distribution metrics are cornerstones of conservation planning, for example, in establishing extinction risk and selecting priority areas, but abundance data are scarce and costly to obtain in comparison to those on species occurrence. Occurrence records, often from citizen science or nonsystematic surveys, are increasingly used to model species’ distributions using environmental predictors. Methods to relate occurrence models to abundance, and therefore, provide greater understanding of patterns of abundance across species’ ranges and population size estimates could bring important benefits for conservation decisions. This thesis aims to develop tools, combining different analytical techniques, field data and GIS, to provide improved estimates of species distribution and abundance in support of extinction risk assessments in threatened Neotropical bird species. To achieve this aim, a case study was implemented over the ranges of 14 dry forest birds from the Tumbesian region of Peru –an area of critical conservation importance due to high endemism and severe anthropogenic threats– with the following objectives: to model the distribution of study species (Chapter 2); to estimate local abundance of species across their ranges using covariate Distance sampling (Chapter 3); to explore range-wide variation in abundance (Chapter 4); to explore the relationship between relative probability of occurrence, derived from modelling, and bird abundance, derived from field studies (Chapter 5). First, ensemble species distribution models, using four modelling methods, were built with a median of 150 occurrence records per species, bioclimatic variables and vegetation indices. Modelled Extent of Occurrence, using a 5% omission error threshold to define presence and absence, was compared to existing range estimates used in extinction risk assessment. Additionally, field data were obtained on the local abundance of the study species and habitat characteristics along four 2.5 km transects at 26 sites over the study area. Covariate Distance sampling was used to estimate bird abundances at each site. Where sites represented discrete or delimited units (e.g. protected areas), specific population sizes were estimated. Local abundance was compared across sites and by range core versus edge; spatial autocorrelation was examined with multivariate Mantel tests; and, relationships with environmental variables were examined using Generalised Additive Models. Finally, relationships between abundance estimates, obtained from the field study, and relative probability of occurrence, obtained from distribution models, were tested using correlations, and where significant relationships were found, these were modelled using hierarchical logistic regression. Individual species distribution modelling methods performed adequately and coincided highly in terms of ranked correlation but differed in the distribution of their predicted values. Range size estimates, from thresholded models, were generally smaller than, but coincided spatially with, published ranges, with the exception of three species of conservation interest. Local abundance varied by one or two orders of magnitude across sites for almost all species, with abundance not necessarily highest at the centre of species’ ranges. Sites of maximum abundance for individual species did not coincide – nine different sites held the highest densities of at least one species. Eleven of 14 species showed significant positive correlations between their abundance and modelled occurrence for at least one modelling technique. Modelling techniques are discussed in light of complementing existing techniques to estimate Extent of Occurrence for extinction risk assessments. Abundance estimates, using methods that incorporate detectability, can be obtained for rare species over very patchy habitats with relatively low survey effort, using a suitably designed sampling protocol. The extreme variation in species' abundances and the complexity in relationships with environmental variables has conservation implications, for example, in the design of conservationmotivated surveys and regarding the need for multiple reserves to capture high local abundances of key species. The relationship between modelled species' occurrence and local abundance is a promising area of research with a view to obtaining better abundance information with less survey effort. In terms of biodiversity conservation in north Peru, critical sites are recommended for urgent protection, and updated extinction risk categories are given for threatened species

2018 - The Twenty-third Annual Symposium of Student Scholars

The full program book from the Twenty-third Annual Symposium of Student Scholars, held on April 19, 2018. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1020/thumbnail.jp