Nature apps: Waiting for the revolution

Jepson, Paul; Ladle, Richard J.

doi:10.1007/s13280-015-0712-2

Cited by 55 publications

(18 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several recent studies have shown the power of smartphone applications (apps) in biological research (Adriaens, 2015;August et al, 2015;Jepson & Ladle, 2015). Once introduced into the project, apps raise public engagement, sometimes even by order of magnitude, as the "Leaf-Watch" app for the "Conker Tree Science Project" (Pocock & Evans, 2014) in which citizens were recording damage caused by leaf-mining moths on horse-chestnut in the UK.…”

Section: Tool S For C S Projec Tsmentioning

confidence: 99%

Citizen science and wildlife biology: Synergies and challenges

et al. 2018

View full text Add to dashboard Cite

Citizen science (CS) has evolved over the past decades as a working method involving interested citizens in scientific research, for example by reporting observations, taking measurements or analysing data. In the past, research on animal behaviour has been benefitting from contributions of citizen scientists mainly in the field of ornithology but the full potential of CS in ecological and behavioural sciences is surely still untapped. Here, we present case studies that successfully applied CS to research projects in wildlife biology and discuss potentials and challenges experienced. Our case studies cover a broad range of opportunities: largescale CS projects with interactive online tools on bird song dialects, engagement of stakeholders as citizen scientists to reduce human-wildlife conflicts, involvement of students of primary and secondary schools in CS projects as well as collaboration with the media leading to successful recruitment of citizen scientists. Each case study provides a short overview of the scientific questions and how they were approached to showcase the potentials and challenges of CS in wildlife biology.Based on the experience of the case studies, we highlight how CS may support research in wildlife biology and emphasise the value of fostering communication in CS to improve recruitment of participants and to facilitate learning and mutual trust among different groups of interest (e.g., researchers, stakeholders, students).We further show how specific training for the participants may be needed to obtain reliable data. We consider CS as a suitable tool to enhance research in wildlife biology through the application of open science procedures (i.e., open access to articles and the data on publicly available repositories) to support transparency and sharing experiences.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Section: Tool S For C S Projec Tsmentioning

confidence: 99%

Citizen science and wildlife biology: Synergies and challenges

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Computer-aided taxonomy enables reliable biological data to be derived from the observations of even unskilled citizens. In the Google Play store, Jepson and Ladle (2015) find numerous apps for automated species identification, for example automated acoustic species detection and identification, and the use of image recognition software to automatically identify tree species from their leaves. Data quality from citizen observers can be improved by automated feedback (Van der Wal et al, 2016).…”

Section: Conservation By Algorithmmentioning

confidence: 99%

Geographies of conservation II: Technology, surveillance and conservation by algorithm

Adams

2017

Progress in Human Geography

102

View full text Add to dashboard Cite

The wide range of wildlife tracking and surveillance technologies (radio and satellite tracking, cameras, and audio) that are being deployed in conservation have important implications for a geographical understanding of care for non-human nature. This report explores four dimensions of their influence. First, their detailed view of spatial dimensions of non-human lives affects conservation's demarcation and control of space. Second, the application of surveillance technologies to people is central to the rise of coercive conservation strategies. Third, such technologies enable the creation and commoditization of spectacular nature. Fourth, spatial digital data enables the automation of conservation decisions, a trend described here as 'conservation by algorithm'.

show abstract

“…Apps on mobile devices are ubiquitous, and often within a person's reach 24-7. Using these to support augmented reality could also provide an interface to generate more detailed data with real-time diagnostics [64][65][66]. In addition, apps that 'gamify' nature can motivate the public to interact with their environment, and thus provide more data on species and the environment.…”

Section: Apps and Gamesmentioning

confidence: 99%

iEcology: Harnessing Large Online Resources to Generate Ecological Insights

Jarić

Correia

Brook

et al. 2020

Trends in Ecology & Evolution

Self Cite

165

129

View full text Add to dashboard Cite

Digital data are accumulating at unprecedented rates. These contain a lot of information about the natural world, some of which can be used to answer key ecological questions. Here, we introduce iEcology (i.e., internet ecology), an emerging research approach that uses diverse online data sources and methods to generate insights about species distribution over space and time, interactions and dynamics of organisms and their environment, and anthropogenic impacts. We review iEcology data sources and methods, and provide examples of potential research applications. We also outline approaches to reduce potential biases and improve reliability and applicability. As technologies and expertise improve, and costs diminish, iEcology will become an increasingly important means to gain novel insights into the natural world. Information Age, Big Data, and iEcologyThe information age is characterized by rapid accumulation of myriad types of digital data [1]. Central to this revolution is the Internet, which is a source of unprecedented amounts of diverse and readily accessible data, via webpages, social media, and various other data platforms. These data are constantly created and stored in the digital realm and form an omnipresent part of the modern world. They also provide novel opportunities for research that the scientific community is only beginning to explore. Here, we describe an emerging research approach -iEcology (i.e., internet ecology), which we define as the study of ecological patterns and processes using online data generated for other purposes and stored digitally (Figure 1). These data can be used to address fundamental ecological questions and to analyze ecological processes at a range of spatiotemporal scales and across a diverse range of contexts. As such, iEcology has the potential to provide new understandings of ecological dynamics and mechanisms, complementing more traditional methods of obtaining ecological data.While iEcology can be considered to fit within the wider scope of ecological informatics (see Glossary), it is distinct from other uses of Big Data sources in the biological sciences in that data are not specifically and intentionally generated to address ecological and environmental questions [2][3][4]. Moreover, iEcology expands on the traditional scope of ecological informatics with new data sources and dedicated methods to analyze them. iEcology is predominantly focused on collecting, collating, and exploring data generated online by human society, either passively or unintentionally (e.g., Internet search activity, social media interactions, and uploaded data and media), a process also referred to as passive crowdsourcing [5]. iEcology uses digital methods to access, handle, and analyze these data, in a manner akin to techniques from other research fields such as sociology, culture and media studies, biomedical sciences, computer sciences, and economics [6,7]. iEcology also shares part of its toolbox with conservation culturomicsan emerging research area in conservation science [8-10]alb...

show abstract

Nature apps: Waiting for the revolution

Cited by 55 publications

References 13 publications

Citizen science and wildlife biology: Synergies and challenges

Citizen science and wildlife biology: Synergies and challenges

Geographies of conservation II: Technology, surveillance and conservation by algorithm

iEcology: Harnessing Large Online Resources to Generate Ecological Insights

Contact Info

Product

Resources

About