Abstract Phytoplankton species are essential bioindicators for evaluating the status of freshwater ecosystems in accordance with the EU Water Framework Directive. However, manual identification of phytoplankton is time‐consuming and requires taxonomic expertise. Deep learning (DL) offers promising tools…
Abstract Plant phenology plays a pivotal role in understanding the interactions between plants and their environment. Despite increasing interest in plant phenology research, documenting their spatial and temporal variability at large spatial scales remains a challenge for many species and a variety…
SUMMARY Plant leaves play a pivotal role in automated species identification using deep learning (DL). However, achieving reproducible capture of leaf variation remains challenging due to the inherent “black box” problem of DL models. To evaluate the effectiveness of DL in capturing leaf shape, we used…
Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly applies to groups characterized by intricate evolutionary…
Abstract Phenological shifts across plant species is a powerful indicator to quantify the effects of climate change. Today, mobile applications with automated species identification open new possibilities for phenological monitoring across space and time. Here, we introduce an innovative spatio‐temporal…
Plant phenology plays a vital role in assessing climate change. To monitor this, individual plants are traditionally visited and observed by trained volunteers organized in national or international networks - in Germany, for example, by the German Weather Service, DWD. However, their number of observers…
We present a multidisciplinary forest ecosystem 3D perception dataset. The dataset was collected in the Hainich-Dün region in central Germany, which includes two dedicated areas, which are part of the Biodiversity Exploratories - a long term research platform for comparative and experimental biodiversity…
Abstract Accurate species identification is essential for ecological monitoring and biodiversity conservation. Interactive plant identification keys have been considerably improved in recent years, mainly by providing iconic symbols, illustrations, or images for the users, as these keys are also commonly…
Poaceae represent one of the largest plant families in the world. Many species are of great economic importance as food and forage plants while others represent important weeds in agriculture. Although a large number of studies currently address the question of how plants can be best recognized on images,…
Deep learning algorithms classify plant species with high accuracy, and smartphone applications leverage this technology to enable users to identify plant species in the field. The question we address here is whether such crowd-sourced data contain substantial macroecological information. In particular,…
Being able to identify plant species is an important factor for understanding biodiversity and its change due to natural and anthropogenic drivers. We discuss the freely available Flora Incognita app for Android, iOS and Harmony OS devices that allows users to interactively identify plant species and…
Digital plant images are becoming increasingly important. First, given a large number of images deep learning algorithms can be trained to automatically identify plants. Second, structured image-based observations provide information about plant morphological characteristics. Finally in the course of…
Background
Deep learning algorithms for automated plant identification need large quantities of precisely labelled images in order to produce reliable classification results. Here, we explore what kind of perspectives and their combinations contain more characteristic information and therefore allow…
Background: Predicting a list of plant taxa most likely to be observed at a given geographical location and time is useful for many scenarios in biodiversity informatics. Since efficient plant species identification is impeded mainly by the large number of possible candidate species, providing a shortlist…
Current rates of species loss triggered numerous attempts to protect and conserve biodiversity. Species conservation, however, requires species identification skills, a competence obtained through intensive training and experience. Field researchers, land managers, educators, civil servants, and the…
Background:
Automated species identification is a long term research subject. Contrary to flowers and fruits, leaves are available throughout most of the year. Offering margin and texture to characterize a species, they are the most studied organ for automated identification. Substantially matured…