Pierre Bonnet

Pierre Bonnet
Cirad - La recherche agronomique pour le développement | CIRAD · Unité Mixte de Recherche Botanique et Bio-Informatique de l’Architecture des Plantes (AMAP)

Phd
I work as a plant scientist at Cirad in the context of which I coordinate the Pl@ntNet citizen science platform

About

123
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Publications

Publications (123)
Article
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming liv...
Article
Full-text available
There is a growing acknowledgement that citizen observatories, and other forms of citizengenerated data, have a significant role in tracking progress towards the Sustainable Development Goals. This is evident in the increasing number of Sustainable Development Goals’ indicators for which such data are already being used and in the high-level recogn...
Article
Full-text available
Species Distribution Models (SDMs) are fundamental tools in ecology for predicting the geographic distribution of species based on environmental data. They are also very useful from an application point of view, whether for the implementation of conservation plans for threatened species or for monitoring invasive species. The generalizability and s...
Article
Full-text available
Species Distribution Models (SDMs) are widely used numerical tools that rely on correlations between geolocated presences (and possibly absences) and environmental predictors to model the ecological preferences of species. Recently, SDMs exploiting deep learning and remote sensing images have emerged and have demonstrated high predictive performanc...
Article
Full-text available
A better knowledge of tree vegetative growth phenology and its relationship to environmental variables is crucial to understanding forest growth dynamics and how climate change may affect it. Less studied than reproductive structures, vegetative growth phenology focuses primarily on the analysis of growing shoots, from buds to leaf fall. In tempera...
Article
Full-text available
Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manuall...
Article
Full-text available
Pl@ntnet is a citizen observatory that relies on artificial intelligence (AI) technologies to help people identify plants with their smartphones (Joly 2014). Over the past few years, Pl@ntNet has become one of the largest plant biodiversity observatories in the world with several million contributors (Bonnet 2020b). Based on user demands, a set of...
Chapter
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals is hindering the aggregation of new data and knowledge. Identifying and naming living plan...
Article
Full-text available
Automated plant identification has recently improved significantly due to advances in deep learning and the availability of large amounts of field photos. As an illustration, the classification accuracy of 10K species measured in the LifeCLEF challenge (Goëau et al. 2018) reached 90%, very close to that of human experts. However, the profusion of f...
Article
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Field photographs of plant species are crucial for research and conservation, but the lack of a centralized database makes them difficult to locate. We surveyed 25 online databases of field photographs and found that they harboured only about 53% of the approximately 125,000 vascular plant species of the Americas. These results reflect the urg...
Article
Full-text available
Field photographs of plant species are crucial for research and conservation, but the lack of a centralized database makes them difficult to locate. We surveyed 25 online databases of field photographs and found that they harboured only about 53% of the approximately 125,000 vascular plant species of the Americas. These results reflect the urgent n...
Article
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants and animals is hindering the aggregation of new data and knowledge. Identifying and naming living pla...
Article
Full-text available
Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, we expected that CNN can grasp how local landscape structure affects prediction of species occurrence in SDMs. The mod...
Chapter
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...
Chapter
Species distribution models (SDM) assess and predict how species spatial distributions depend on the environment, due to species ecological preferences. These models are used in many different scenarios such as conservation plans or monitoring of invasive species. The choice of a model and of environmental data have strong impact on the model’s abi...
Article
Full-text available
- Building reliable Species Distribution Models (SDMs) from presence-only information requires a good understanding of the spatial variation in the sampling effort. However, in most cases the sampling effort is unknown, leading to biases in SDMs. This study proposes a method to jointly estimate the parameters of sampling effort and species densitie...
Article
Full-text available
0000−0002−2161−9940] , Hervé Goëau 2[0000−0003−3296−3795] , Stefan Kahl 7 , Hervé Glotin 4[0000−0001−7338−8518] , Elijah Cole 10[0000−0001−6623−0966] , Benjamin Deneu 1[0000−0003−0640−5706] , Maximillien Servajean 8[0000−0002−9426−2583] , Titouan Lorieul 1[0000−0001−5228−9238] , Willem-Pier Vellinga 5 , Pierre Bonnet 2[0000−0002−2828−4389] , Ivan E...
Article
Full-text available
Plant diseases have a significant impact on global food security and the world's agricultural economy. Their early detection and classification increase the chances of setting up effective control measures, which is why the search for automatic systems that allow this is of major interest to our society. Several recent studies have reported promisi...
Article
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Coffee is a beverage enjoyed by millions of people worldwide and an important commodity for millions of people. Beside the two cultivated species (Coffea arabica and Coffea canephora), the 139 wild coffee species/taxa belonging to the Coffea genus are largely unknown to coffee scientists and breeders although these species may be crucial for future...
Article
Full-text available
The diversity of habitats in the Cévennes national Park is home to a rich flora, comprising more than 2400 species (angiosperms, gymnosperms, and ferns). A good knowledge of this flora is essential for the development of adapted management strategies. However, human resources for this purpose are limited, and the support of residents and visitors c...
Article
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The increasing availability of digital images, coupled with sophisticated artificial intelligence (AI) techniques for image classification, presents an exciting opportunity for biodiversity researchers to create new datasets of species observations. We investigated whether an AI plant species classifier could extract previously unexploited biodiver...
Article
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Pl@ntNet is a scientific and citizen platform based on artificial intelligence techniques to help participants more easily identify plants with their smartphones. The identification of plant species is indeed an important step for many scientific, educational and land management activities (for natural or cultivated spaces). This step, which is int...
Book
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...
Article
Full-text available
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 pub...
Chapter
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...
Article
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and nami...
Article
Full-text available
Phenology—the timing of life-history events—is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current practice of manually harvesting data from individual specime...
Article
Full-text available
Premise: Weed removal in agriculture is typically achieved using herbicides. The use of autonomous robots to reduce weeds is a promising alternative solution, although their implementation requires the precise detection and identification of crops and weeds to allow an efficient action. Methods: We trained and evaluated an instance segmentation...
Article
Full-text available
Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as...
Preprint
Full-text available
Phenology, the timing of life-history events, is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current practice of manually harvesting data from individual speci...
Article
Full-text available
Premise: Herbarium specimens represent an outstanding source of material with which to study plant phenological changes in response to climate change. The fine-scale phenological annotation of such specimens is nevertheless highly time consuming and requires substantial human investment and expertise, which are difficult to rapidly mobilize. Meth...
Article
Full-text available
The use of naturalist mobile applications has dramatically increased during last years, and provides huge amounts of accurately geolocated species presences records. Integrating this novel type of data in species distribution models (SDMs) raises specific methodological questions. Presence-only SDM methods require background points, which should be...
Preprint
Full-text available
Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relationship between an environment and the species which may be found there. To facilitate research in this area, we present the GeoLifeCLEF 2020 dataset, which consists of 1.9...
Chapter
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...
Article
Con base en las recientes aplicaciones exitosas de técnicas de Aprendizaje Profundo en la clasificación, detección y segmentación de plantas, proponemos un enfoque de segmentación de instancias utilizando un modelo Mask R-CNN para la detección de malezas y cultivos en tierras de cultivo. Evaluamos el rendimiento de nuestro modelo con la métrica de...
Article
Full-text available
The control of plant diseases is a major challenge to ensure global food security and sustainable agriculture. Several recent studies have proposed to improve existing procedures for early detection of plant diseases through modern automatic image recognition systems based on deep learning. In this article, we study these methods in detail, especia...
Conference Paper
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and nami...
Article
Pl@ntNet is a scientific and citizen platform based on artificial intelligence techniques to help participants more easily identify plants with their smartphones. The identification of plant species is indeed an important step for many scientific, educational and land management activities (for natural or cultivated spaces). This step, which is int...
Article
Full-text available
La diversité des habitats du Parc national des Cévennes héberge une flore riche, composée de plus de 2400 espèces (angiospermes, gymnospermes et fougères). Une bonne connaissance de cette flore est essentielle pour le développement de stratégies de gestion adaptées. Les ressources humaines étant cependant limitées, l’appui des résidents et visiteur...
Article
This dataset is the result of using an AI image classifer to classify images of plants on social media. We believe this is the first AI validated dataset of biological records taken from social media. This represents the dawn of AI naturalists whose domain of exploration is not the outdoor world but the digital realm. These AI naturalists will traw...
Chapter
Full-text available
Identifying and naming living plants or animals is usually impossible for the general public and often a difficult task for professionals and naturalists. Bridging this gap is a key challenge towards enabling effective biodiversity information retrieval systems. This taxonomic gap was actually already identified as one of the main ecological challe...
Chapter
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. Unfortunately, such basic information is often only partially available for professional stakeholders, teachers, scientists and citizens, and o...
Article
Full-text available
Millions of herbarium records provide an invaluable legacy and knowledge of the spatial and temporal distributions of plants over centuries across all continents (Soltis et al. 2018). Due to recent efforts to digitize and to make publicly accessible most major natural collections, investigations of ecological and evolutionary patterns at unpreceden...
Conference Paper
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. However, the burden of the routine identification of plants and animals in the field is strongly penalizing the aggregation of new data and kno...
Chapter
Full-text available
Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. However, the burden of the routine identification of plants and animals in the field is strongly penalizing the aggregation of new data and kno...
Article
Full-text available
Premise of the Study Phenological annotation models computed on large‐scale herbarium data sets were developed and tested in this study. Methods Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time‐consuming, requires substantial human investm...
Book
Full-text available
AcknowledgementsThe organization of the PlantCLEF task is supported by the French project Floris’Tic (Tela Botanica, INRIA, CIRAD, INRA, IRD) funded in the context of the national investment program PIA. The organization of the BirdCLEF task is supported by the Xeno-Canto foundation for nature sounds as well as the French CNRS project SABIOD.ORG an...
Experiment Findings
Full-text available
The GeoLifeCLEF challenge provides a testbed for the system-oriented evaluation of a geographic species recommendation service. The aim is to investigate location-based recommendation approaches in the context of large scale spatialized environmental data. This paper presents an overview of the resources and assessments of the GeoLifeCLEF task 2018...
Chapter
Full-text available
Species distribution models (SDM) are widely used for ecological research and conservation purposes. Given a set of species occurrence, the aim is to infer its spatial distribution over a given territory. Because of the limited number of occurrences of specimens, this is usually achieved through environmental niche modeling approaches, i.e. by pred...
Chapter
The estimated number of flowering plant species on Earth is around 400,000. In order to classify all known species via automated image-based approaches, current datasets of plant images will have to become considerably larger. To achieve this, some authors have explored the possibility of using herbarium sheet images. As the plant datasets grow and...
Chapter
Automated identification of plants and animals have improved considerably in the last few years, in particular thanks to the recent advances in deep learning. The next big question is how far such automated systems are from the human expertise. Indeed, even the best experts are sometimes confused and/or disagree between each others when validating...