How citizen scientists contribute to monitor protected areas thanks to automatic plant identification tools. Issue 2 (11th September 2020)
- Record Type:
- Journal Article
- Title:
- How citizen scientists contribute to monitor protected areas thanks to automatic plant identification tools. Issue 2 (11th September 2020)
- Main Title:
- How citizen scientists contribute to monitor protected areas thanks to automatic plant identification tools
- Authors:
- Bonnet, Pierre
Joly, Alexis
Faton, Jean‐Michel
Brown, Susan
Kimiti, David
Deneu, Benjamin
Servajean, Maximilien
Affouard, Antoine
Lombardo, Jean‐Christophe
Mary, Laura
Vignau, Christel
Munoz, François - Abstract:
- Abstract: 1. Successful monitoring and management of plant resources worldwide needs the involvement of civil society to support natural reserve managers. Because it is difficult to correctly and quickly identify plant species for non‐specialists, the development of recent techniques based on automatic visual identification should facilitate and increase public engagement in citizen science initiatives. 2. Automatic identification platforms are new to most citizen scientists and land managers. Pl@ntNet is such a platform, available since 2013 on web and mobile environments, and now included in several workflows such as invasive alien species management, endemic species monitoring, educational activities and eco‐tourism practices. The successful development of such platforms needs to identify their strengths and weaknesses in order to improve and facilitate their use in all aspects of ecosystem management. 3. Here we present two Pl@ntNet citizen science initiatives used by conservation practitioners in Europe (France) and Africa (Kenya). We discuss various perspectives, including benefits and limitations. Based on the experiences of field managers, we formulate several recommendations for future initiatives. The recommendations are aimed at a diverse group of conservation managers and citizen science practitioners. Abstract : Data acquisition and management workflow implemented in the two analyzed case studies. In the Ramières Reserve, pioneer citizen scientists (i.e CitizenAbstract: 1. Successful monitoring and management of plant resources worldwide needs the involvement of civil society to support natural reserve managers. Because it is difficult to correctly and quickly identify plant species for non‐specialists, the development of recent techniques based on automatic visual identification should facilitate and increase public engagement in citizen science initiatives. 2. Automatic identification platforms are new to most citizen scientists and land managers. Pl@ntNet is such a platform, available since 2013 on web and mobile environments, and now included in several workflows such as invasive alien species management, endemic species monitoring, educational activities and eco‐tourism practices. The successful development of such platforms needs to identify their strengths and weaknesses in order to improve and facilitate their use in all aspects of ecosystem management. 3. Here we present two Pl@ntNet citizen science initiatives used by conservation practitioners in Europe (France) and Africa (Kenya). We discuss various perspectives, including benefits and limitations. Based on the experiences of field managers, we formulate several recommendations for future initiatives. The recommendations are aimed at a diverse group of conservation managers and citizen science practitioners. Abstract : Data acquisition and management workflow implemented in the two analyzed case studies. In the Ramières Reserve, pioneer citizen scientists (i.e Citizen scientistA ) have provided a large volume of visual data to allow accurate automatic identification by reserve managers and local citizen scientists (i.e Citizen scientistB ), which yields reliable observation data. For the Lewa Conservatory, the Lewa House and the Lewa Conservancy have contextualized a Pl@ntNet platform restricted to a reference species list, and have produced a large amount of observations to initiate the automatic identification service on Lewa flora. Abstract: 1. La réussite de la surveillance et de la gestion des ressources végétales dans le monde entier nécessite l'implication de la société civile pour soutenir les gestionnaires des réserves naturelles. Parce qu'il est difficile d'identifier correctement et rapidement les espèces végétales pour les non‐spécialistes, le développement de techniques récentes basées sur l'identification visuelle automatique devrait faciliter et accroître l'engagement du public dans les initiatives scientifiques citoyennes. 2. Les plate‐formes d'identification automatique sont nouvelles pour la plupart des scientifiques citoyens et des gestionnaires des territoires. La plateforme Pl@ntNet, disponible depuis 2013 sur le web et les environnements mobiles, et désormais incluse dans plusieurs dispositifs professionnels tels que la gestion des espèces exotiques envahissantes, la surveillance des espèces endémiques, les activités éducatives et les pratiques éco‐touristiques. La réussite du développement de telles plate‐formes nécessite d'identifier leurs forces et faiblesses afin d'améliorer et de faciliter leur utilisation dans tous les aspects de la gestion des écosystèmes. 3. Nous présentons ici deux initiatives scientifiques et citoyennes de Pl@ntNet, utilisées par les praticiens de la conservation en Europe (France) et en Afrique (Kenya). Nous discutons plusieurs perspectives, en y incluant les avantages et les limites. Sur la base des expériences de terrain des gestionnaires, nous formulons plusieurs recommandations pour des initiatives futures similaires. Ces recommandations s'adressent à un groupe diversifié de gestionnaires de la conservation et de praticiens des sciences citoyennes. … (more)
- Is Part Of:
- Ecological solutions and evidence. Volume 1:Issue 2( 2020)
- Journal:
- Ecological solutions and evidence
- Issue:
- Volume 1:Issue 2( 2020)
- Issue Display:
- Volume 1, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 1
- Issue:
- 2
- Issue Sort Value:
- 2020-0001-0002-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-09-11
- Subjects:
- artificial intelligence -- automatic plant identification -- citizen science -- deep learning technologies -- opportunistic data -- plant biodiversity monitoring -- public engagement -- volunteers -- intelligence artificielle -- identification automatique des plantes -- science citoyenne -- technologies d'apprentissage profond -- données opportunistes -- surveillance de la biodiversité végétale -- engagement du public -- volontaires
Environmental management -- Periodicals
Ecology -- Periodicals
Electronic journals
Periodicals
333.72 - Journal URLs:
- https://besjournals.onlinelibrary.wiley.com/journal/26888319 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/2688-8319.12023 ↗
- Languages:
- English
- ISSNs:
- 2688-8319
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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