Traits and phylogenies modulate the environmental responses of wood-inhabiting fungal communities across spatial scales

Identifying the spatial scales at which community assembly processes operate is fundamental for gaining a mechanistic understanding of the drivers shaping ecological communities. In this study, we examined whether and how traits and phylogenetic relationships structure fungal community assembly across spatial scales. We applied joint species distribution modelling to a European-scale dataset on 215 wood-inhabiting fungal species, which includes data on traits, phylogeny and environmental variables measured at the local (log-level) and regional (site-level) scales. At the local scale, wood-inhabiting fungal communities were mostly structured by deadwood decay stage, and the trait and phylogenetic patterns along this environmental gradient suggested the lack of diversifying selection. At regional scales, fungal communities and their trait distributions were influenced by climatic and connectivity-related variables. The fungal climatic niches were not phylogenetically structured, suggesting that diversifying selection or stabilizing selection for climatic niches has played a strong role in wood-inhabiting communities. In contrast, we found a strong phylogenetic signal in the responses to connectivity-related variables, revealing phylogenetic homogenization in small and isolated forests. Synthesis. Altogether, our results show that species-level traits and phylogenies modulate the responses of wood-inhabiting fungi to environmental processes acting at different scales. This result suggests that the evolutionary histories of fungal traits diverge along different environmental axes.Peer reviewe

Overview of FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem

The main goal of the new LifeCLEF challenge, FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem, was to provide an evaluation ground for end-to-end fungi species recognition in an open class set scenario. An AI-based fungi species recognition system deployed in the Atlas of Danish Fungi helps mycologists to collect valuable data and allows users to learn about fungi species identification. Advances in fungi recognition from images and metadata will allow continuous improvement of the system deployed in this citizen science project. The training set is based on the Danish Fungi 2020 dataset and contains 295,938 photographs of 1,604 species. For testing, we provided a collection of 59,420 expert-approved observations collected in 2021. The test set includes 1,165 species from the training set and 1,969 unknown species, leading to an open-set recognition problem. This paper provides (i) a description of the challenge task and datasets, (ii) a summary of the evaluation methodology, (iii) a review of the systems submitted by the participating teams, and (iv) a discussion of the challenge results. © 2022 Copyright for this paper by its authors

Dataset on species incidence, species richness and forest characteristics in a Danish protected area

The data presented in this article are related to the research article entitled “Restoring hydrology and old-growth structures in a former production forest: Modelling the long-term effects on biodiversity” (A. Mazziotta, J. Heilmann-Clausen, H. H.Bruun, Ö. Fritz, E. Aude, A.P. Tøttrup) [1]. This article describes how the changes induced by restoration actions in forest hydrology and structure alter the biodiversity value of a Danish forest reserve. The field dataset is made publicly available to enable critical or extended analyses

Automatic Fungi Recognition: Deep Learning Meets Mycology

The article presents an AI-based fungi species recognition system for a citizen-science community. The system’s real-time identification too — FungiVision — with a mobile application front-end, led to increased public interest in fungi, quadrupling the number of citizens collecting data. FungiVision, deployed with a human-in-the-loop, reaches nearly 93% accuracy. Using the collected data, we developed a novel fine-grained classification dataset — Danish Fungi 2020 (DF20) — with several unique characteristics: species-level labels, a small number of errors, and rich observation metadata. The dataset enables the testing of the ability to improve classification using metadata, e.g., time, location, habitat and substrate, facilitates classifier calibration testing and finally allows the study of the impact of the device settings on the classification performance. The continual flow of labelled data supports improvements of the online recognition system. Finally, we present a novel method for the fungi recognition service, based on a Vision Transformer architecture. Trained on DF20 and exploiting available metadata, it achieves a recognition error that is 46.75% lower than the current system. By providing a stream of labeled data in one direction, and an accuracy increase in the other, the collaboration creates a virtuous cycle helping both communities

Handbook for the measurement of macrofungal functional traits : A start with basidiomycete wood fungi

Functional traits are widely recognized as a useful framework for testing mechanisms underlying species community assemblage patterns and ecosystem processes. Functional trait studies in the plant and animal literature have burgeoned in the past 20 years, highlighting a need for standardized ways to measure ecologically meaningful traits across taxa and ecosystems. However, standardized measurements of functional traits are lacking for many organisms and ecosystems, including fungi. Basidiomycete wood fungi occur in all forest ecosystems world-wide, where they are decomposers and also provide food or habitat for other species, or act as tree pathogens. Despite their major role in the functioning of forest ecosystems, the understanding and application of functional traits in studies of communities of wood fungi lags behind other disciplines. As the research field of fungal functional ecology is growing, there is a need for standardized ways to measure fungal traits within and across taxa and spatial scales. This handbook reviews pre-existing fungal trait measurements, proposes new core fungal traits, discusses trait ecology in fungi and highlights areas for future work on basidiomycete wood fungi. We propose standard and potential future methodologies for collecting traits to be used across studies, ensuring replicability and fostering between-study comparison. Combining concepts from fungal ecology and functional trait ecology, methodologies covered here can be related to fungal performance within a community and environmental setting. This manuscript is titled "a start with" as we only cover a subset of the fungal community here, with the aim of encouraging and facilitating the writing of handbooks for other members of the macrofungal community, for example, mycorrhizal fungi. A is available for this article.Peer reviewe

Danish Fungi 2020 - Not Just Another Image Recognition Dataset

We introduce a novel fine-grained dataset and bench-mark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, and well-defined class hierarchy. DF20 has zero overlap with ImageNet, al-lowing unbiased comparison of models fine-tuned from publicly available ImageNet checkpoints. The proposed evaluation protocol enables testing the ability to improve classification using metadata - e.g. precise geographic location, habitat, and substrate, facilitates classifier calibration testing, and finally allows to study the impact of the device settings on the classification performance. Experiments using Convolutional Neural Networks (CNN) and the recent Vision Transformers (ViT) show that DF20 presents a challenging task. Interestingly, ViT achieves results su-perior to CNN baselines with 80.45% accuracy and 0.743 macro F1 score, reducing the CNN error by 9% and 12% respectively. A simple procedure for including metadata into the decision process improves the classification accuracy by more than 2.95 percentage points, reducing the error rate by 15%. The source code for all methods and experiments is available at https://sites.google.com/view/danish-fungi-dataset

A Fungal Perspective on Conservation Biology

Hitherto fungi have rarely been considered in conservation biology, but this is changing as the field moves from addressing single species issues to an integrative ecosystem-based approach. The current emphasis on biodiversity as a provider of ecosystem services throws the spotlight on the vast diversity of fungi, their crucial roles in terrestrial ecosystems, and the benefits of considering fungi in concert with animals and plants. We reviewed the role of fungi in ecosystems and composed an overview of the current state of conservation of fungi. There are 5 areas in which fungi can be readily integrated into conservation: as providers of habitats and processes important for other organisms; as indicators of desired or undesired trends in ecosystem functioning; as indicators of habitats of conservation value; as providers of powerful links between human societies and the natural world because of their value as food, medicine, and biotechnological tools; and as sources of novel tools and approaches for conservation of megadiverse organism groups. We hope conservation professionals will value the potential of fungi, engage mycologists in their work, and appreciate the crucial role of fungi in nature

The effects of habitat degradation on metacommunity structure of wood-inhabiting fungi in European beech forests

Intensive forest management creates habitat degradation by reducing the variation of forest stands in general, and by removing old trees and dead wood in particular. Non-intervention forest reserves are commonly believed to be the most efficient tool to counteract the negative effects on biodiversity, but actual knowledge of the conservation efficiency is limited, especially for recent reserves. The structure of ecological communities is often described with measures of nestedness, beta diversity and similarity between communities. We studied whether these measures differ among forest reserves with different management histories. For this purpose, we used a large data set of wood-inhabiting fungi collected from dead beech trees in European beech-dominated forest reserves. The structure of fungal assemblages showed high beta diversity, while nestedness and similarity was low. During the decomposition process of trees beta diversity between the communities occupying different trees increased in natural, but not in previously managed sites. Effects of management and decay process on nestedness were complex. We argue that the detected differences most likely reflect historical effects which have extirpated specialized species from the local species pools in managed sites, and resulted in more homogeneous communities in managed sites. It is alarming that community structure is affected the most in the latest decay stages where the decay process turns the dead wood into litter, and which is thus the interface between the wood decay and the litter-decaying ecosystem. The effects of simplified communities in late decay stages on soil biodiversity should be studied