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Microhabitats are embedded in mesohabitats and provide special niches for particular species [ 14 ]. Because environmental changes are caused not only by natural but also by societal processes, by interacting and shaping their environment, local communities have developed their own perception of these changes [ 17 ].
Recently, local observations of environmental change are becoming recognized by science [ 18 ]. According to Nakashima et al. In her work, Gantuya et al.
Ujházy et al. The results showed that the two groups shared similar views on perceived landscape changes, but they evaluated these changes differently.
Farmers mostly focused on the impact on habitat usefulness, while conservationists had a primarily eco-centric approach. The common message of studies focusing on folk knowledge in relation to environmental change is the need for a deeper understanding of local perceptions [ 1821 ].
Studying local knowledge could broaden our understanding of the trends in ongoing ecological changes [ 22 ]. Having completed quantitative analysis of a large number of interviews, it is also possible to provide important information on the heterogeneity of social landscape perception [ 20 ].
The few studies that document local and traditional knowledge of fungal habitats and population changes incl. abundance usually focus on individual species [ 2324 ].
Lampman [ 25 ], however, undertakes a complete documentation of fungi-related knowledge shared by the Tzeltal Maya of the Chiapas highlands. In his work, Lampman focuses on knowledge concerning wild edible fungi ecology.
However, the characteristics he describes often only provide a general overview of locally used macrofungi, without any detailed data on particular species. Lampman recorded information on the relationship of particular taxa to characteristics such as substrate preference, but without providing quantitative data e.
number of informants. To document the habitat types used by local Polish mushroom collectors to describe the habitat preferences of various fungal taxa. To document the habitat preference of each mushroom species by appealing to the observations of a large number of mushroom collectors.
To analyse local perception of macrofungal population trends abundance using local observations as a specific form of fungi monitoring.
Mazovia is a historical region that lies in the Central-Eastern part of Poland. Mazovia was an independent principality throughout a major part of Polish mediaeval history [ 26 ]. The region lies mainly within the current borders of the Mazovian Voivodeship and extends to part of the Łódź Voivodeship in the south-west and to Podlasie Voivodeship in the north-east.
It is currently inhabited by around 5. Mazovia is characterized by a cold temperate climate with high annual temperature amplitudes and a transitional character between oceanic and continental [ 29 ].
Forest vegetation covers The other species that are the most abundant in mixed and deciduous forests are Quercus robur L. and Betula pendula Roth. Folk cultural characteristics shared by people living in this historical region are currently difficult to find.
However, the region is still inhabited by a few ethnographic groups. Usually, they can be distinguished by their local traditions and cultures. These groups are the Podlasianie, Mazurzy, Łowiczanie, and Kurpie [ 32 ].
The capital city of Warsaw is situated in the centre of Mazovia. The research was conducted in 38 villages or small market towns, which were dispersed in a km grid throughout the whole Mazovian region Fig.
These were Burakowskie, Całowanie, Chyżyny, Cieciory, Dąbrowa, Faustynowo, Flesze, Gostkowo, Kluki, Klusek, Kocierzew, Konopki Grajewo CountyKonopki Łomża CountyKorytów, Kozietuły, Kręgi, Leksyn, Łątczyn, Łękawica, Mamino, Mchowo, Mistrzewice, Nowy Gołymin, Piaski, Przedświt, Psucin, Pszczonów, Radzymin, Regnów, Sojczyn, Stare Babice, Szczaki, Szydłowo, Świerże, Węgrzynowice, Wyrzyki, Zdunek, and Żurawka currently the district of Sulejówek.
This network of settlements forms part of the larger grid of the Ethnographic Atlas of Poland, which was also used to collect data on mushroom picking between and The field research took place between andfrom April to November—the months of abundance of traditionally collected wild edible fungi in Poland.
Data collection was spread evenly across the research period, while the volume of collected data depended mostly on weather conditions and population density. Data were collected through individual semi-structured interviews conducted among local informants, which constitutes the classic method in ethnobiology [ 33 ].
Aside from data concerning local knowledge on collected species, folk taxonomy and cultural significance presented in previous work [ 34 ], we have also documented knowledge about collected species ecology and their changes in abundance observed during the years of active fungi collection usually since childhood to the day of interview.
Information about macrofungi gathered or recognized as edible was collected by using the freelisting method. All freelists were made orally and written down. Questions relating to knowledge about species habitat and changes to abundance were asked in relation to each listed species.
Not everyone was able to answer them. At least one landscape walk or joined collection trip was conducted in each village.
The majority of voucher specimens for further identification were collected fresh during field interviews, and some were acquired in dried form from respondents. A total of individual interviews have been conducted where respondents provided information on folk taxonomy of collected fungi species [ 34 ].
Among them, respondents provided information on fungal ecology related to 92 taxa. The age of informants ranged from 17 to The selection of informants was haphazard—based on their willingness to participate in the interview—and therefore socio-demographic characteristics were varied.
However, like in most ethnobiological studies, we aimed at talking to middle-aged and older people. The majority of fungal fruiting bodies were identified with the support of mushroom pictures or identification guides [ 36 ]. Some of the interviews were conducted simultaneously with mushroom collection.
This method enabled us to recognize taxa on the spot and to collect voucher specimens, which were additionally identified by DNA barcoding [ 34 ]. All folk habitat terms mentioned by the respondents in the interviews were extracted and grouped.
Synonymous folk habitat names were grouped according to dimensions such as dominant symbiotic species, succession, land use, vegetation structure, forest vegetation physiognomy, geomorphology, soils, hydrology, human, and animal disturbances [ 1516 ]. After analysing interviews and reports concerning particular fungal taxa, we also selected 35 taxa with 5 or more individual ecological descriptions Fig.
In order to present the acquired data, we used Sankey diagram created with the use of Tableau software version The main observed habitat types preferred by certain mushroom species according to local mushroom collectors in Mazovia, Poland.
Colour shows details about habitat. Size of line indicates percentage of respondents mentioning certain habitat in a particular species description. PCA analysis was conducted on the basis of the matrix of the most frequently mentioned habitats in relation to different fungal taxa, which were selected in analysis presented in Fig.
The main purpose of the principal component analysis is to compute the principal components in this case elements describing fungal habitats and use them to determine certain groups of species related to specific multidimentional habitat description.
This allows for a reduction in the dimensionality of data while preserving its variation. The first principal components can define which direction maximizes the variation of projected points, therefore enabling the division of certain fungal species into groups with similar habitat preferences.
Data processing included normalization using the min-max scaling method and singular value decomposition SVD.
PCA analysis was performed in R programming language using the FactoMineR package in Rstudio software [ 37 ] Fig. This was supplemented with data from other scientific publications.
: Mushroom Ecology Study| Aspen’s take on fungi at work… maintaining an ecological balance in our woods and forests. | Collaboration with Experts: Collaborate with local mycological experts, conservation organizations, and land managers to gain insights into sustainable mushroom harvesting practices. Seek guidance on species identification, conservation priorities, and areas where harvesting can be conducted in a sustainable manner. Work together to establish guidelines and best practices for sustainable mushroom harvesting in your region. By following these principles of sustainable mushroom harvesting, we can enjoy the benefits of mushroom foraging while ensuring the preservation and sustainability of these valuable fungal resources. Responsible harvesting practices contribute to the conservation of mushroom biodiversity, the health of ecosystems, and the enjoyment of future generations. Obtain Proper Knowledge: Before embarking on a foraging trip, educate yourself about local regulations, permits, and any protected species or habitats in the area. Familiarize yourself with the different mushroom species, their habitats, and identification features. Consider joining local mycological societies or attending workshops to enhance your knowledge. Leave No Trace: Practice Leave No Trace principles while foraging. Minimize your impact by staying on designated trails or paths and avoiding trampling vegetation or damaging tree roots. Refrain from removing or damaging other plant species, as they play a crucial role in supporting mushroom populations and ecosystem balance. Responsible Harvesting: Harvest mushrooms in a responsible and sustainable manner. Only collect mature specimens, leaving behind younger or immature ones to allow for spore dispersal and future reproduction. Avoid over-harvesting from a single location to ensure the survival and regeneration of mushroom populations. Respect any local regulations on harvest limits or protected species. Avoid pulling or uprooting mushrooms, as this can damage the mycelium and disturb the surrounding habitat. Cutting allows the mycelium to remain intact and continue its essential ecological functions. Minimize Disturbance: Take care not to disturb the natural environment while foraging. Avoid digging, raking, or disturbing soil or leaf litter unnecessarily, as this can disrupt the habitat and affect the mycelium and other organisms living in the area. Be Mindful of Ecosystems: Be mindful of the ecosystems in which mushrooms grow. Some habitats, such as old-growth forests or sensitive ecosystems, may require extra caution and limited impact. Avoid trampling delicate flora, damaging trees or shrubs, or disturbing wildlife habitats. Share Knowledge Responsibly: If you come across rare, endangered, or sensitive mushroom species, avoid disclosing their exact locations publicly. Sharing such information may lead to overharvesting or habitat destruction. Instead, share your findings with local mycological experts, conservation organizations, or land managers who can assess the situation and take appropriate conservation measures. Respect Private and Protected Lands: Obtain proper permissions and respect any restrictions when foraging on private or protected lands. Follow designated trails and areas and adhere to any specific guidelines or regulations provided by landowners or land management agencies. Document and Report Findings: If you observe rare or unusual mushroom species or notice changes in mushroom populations over time, consider documenting your findings and sharing them with relevant scientific or conservation organizations. Your observations can contribute to the understanding of mushroom ecology, distribution, and potential conservation efforts. Remember, responsible foraging and harvesting practices help preserve mushroom populations, maintain the integrity of their habitats, and ensure the sustainability of this valuable resource for future generations. By being mindful and respectful of nature, you can enjoy the experience of mushroom foraging while minimizing negative impacts. Awareness and Education: Raise awareness about the importance of mushrooms in ecosystems and their conservation needs. Educate the public about the role of citizen science in gathering valuable data for research and conservation efforts. Highlight the benefits of citizen science, such as fostering a sense of connection with nature and contributing to scientific knowledge. Collaborate with Organizations: Partner with local mycological societies, conservation organizations, or research institutions that have established citizen science programs related to mushrooms. Collaborate on projects, share resources, and promote their initiatives to your audience. This collaboration helps leverage existing expertise and ensures that data collected is utilized effectively for conservation purposes. Mushroom Identification and Reporting: Encourage individuals to learn about mushroom identification and report their findings. Provide resources such as field guides, workshops, or online platforms where participants can submit observations and photographs of mushrooms they encounter. Emphasize the importance of accurate species identification and provide guidance on proper documentation techniques. Monitoring Programs: Facilitate citizen science monitoring programs that focus on tracking mushroom populations, distribution, or phenology. Provide training materials, protocols, and data collection tools to participants. Collaborate with experts to develop standardized monitoring methods and ensure the collected data is scientifically valuable and comparable across different locations and time periods. Data Analysis and Research: Facilitate opportunities for citizen scientists to engage in data analysis and contribute to research efforts. Provide access to data repositories, online platforms, or tools for data visualization and analysis. Encourage citizen scientists to collaborate with researchers or participate in data interpretation workshops to enhance their understanding of the scientific process. Community Engagement: Foster a sense of community among citizen scientists through online forums, social media groups, or local gatherings. Create platforms for sharing experiences, knowledge, and insights related to mushroom conservation. Organize field trips, workshops, or conferences where citizen scientists can connect with experts, exchange ideas, and contribute to ongoing conservation efforts. Outreach and Advocacy: Promote the outcomes and impact of citizen science initiatives for mushroom conservation through various communication channels. Share success stories, highlight scientific discoveries, and emphasize the role of citizen scientists in contributing to conservation efforts. Advocate for the integration of citizen science data in policy-making, land management decisions, and conservation planning. By promoting citizen science initiatives for mushroom conservation, we empower individuals to become active contributors to scientific knowledge and conservation efforts. Citizen science not only enhances our understanding of mushroom biodiversity and ecology but also fosters a sense of stewardship and collective responsibility for the preservation of these valuable organisms and their habitats. Data Collection: Citizen scientists actively collect data on mushroom populations, including species occurrence, abundance, and distribution. By exploring forests, parks, and other natural areas, they contribute to a wide-ranging and comprehensive dataset that would be difficult for researchers to gather alone. Their observations help build a more complete picture of mushroom diversity and its changes over time. Increased Geographic Coverage: Citizen scientists cover a wide geographic area, allowing for monitoring in regions that may not be accessible or prioritized by professional researchers. This expanded coverage helps fill knowledge gaps and provides insights into the distribution and abundance of mushroom species across various habitats and ecosystems. Long-Term Monitoring: Citizen scientists often engage in long-term monitoring efforts, returning to the same locations repeatedly over multiple seasons or years. This longitudinal data is invaluable for understanding population dynamics, seasonal variations, and long-term trends in mushroom populations. It provides insights into how mushroom communities respond to environmental changes, climate variability, and land use patterns. Early Detection of Species: With their enthusiasm and local knowledge, citizen scientists can often identify new or rare mushroom species that may be overlooked by professionals. Their keen observations and documentation contribute to the discovery of novel species and provide early detection of species that may be declining or at risk. This information helps prioritize conservation efforts and ensures the protection of vulnerable mushroom populations. Data Quality Assurance: Citizen science projects employ quality control mechanisms to ensure the accuracy and reliability of data collected by participants. Training materials, standardized protocols, and verification processes help maintain data integrity. Collaboration between citizen scientists and experts in the field ensures that data collected aligns with scientific standards and can be utilized for meaningful research and conservation applications. Community Engagement and Education: Citizen science initiatives foster a sense of community and engagement with nature. They provide opportunities for participants to learn about mushroom identification, ecological processes, and conservation principles. By involving the public in scientific research, citizen science projects promote environmental awareness, empower individuals to become stewards of their local ecosystems, and cultivate a deeper appreciation for the natural world. Contribution to Scientific Research: The data collected by citizen scientists can contribute to scientific research in various ways. It can be used to assess the impacts of climate change, habitat degradation, or invasive species on mushroom populations. It can also help identify patterns of species distribution, phenology, and interactions with other organisms. The insights gained from citizen science data contribute to scientific publications, inform conservation strategies, and enhance our understanding of mushroom ecology and biodiversity. In summary, citizen scientists play a vital role in monitoring mushroom populations and contribute to scientific research by collecting data, increasing geographic coverage, engaging in long-term monitoring, identifying new species, ensuring data quality, and fostering community engagement. Their efforts greatly enhance our knowledge of mushroom ecology, aid in conservation planning, and promote a deeper connection between people and the natural world. Ecological Importance: Educating the public about mushroom ecology helps them recognize the vital roles mushrooms play in ecosystems. By understanding their functions in nutrient cycling, decomposition, and symbiotic relationships, people can appreciate the intricate web of life and the interconnectedness of all living organisms. Biodiversity Conservation: Raising awareness about mushroom conservation highlights the need to protect the diverse range of mushroom species. By emphasizing their role in maintaining biodiversity, individuals can grasp the importance of preserving habitats that support mushroom populations. This awareness extends beyond mushrooms to encompass the broader conservation of ecosystems and the myriad species that depend on them. Ecosystem Services: Educating people about the ecosystem services provided by mushrooms creates an appreciation for their contributions. These services include nutrient recycling, soil fertility enhancement, and ecological balance. By understanding the value of these services, individuals are more likely to support conservation efforts and sustainable practices. Threats and Challenges: Increasing awareness about the threats facing mushroom populations, such as habitat loss, pollution, and climate change, helps individuals understand the urgency of conservation. Awareness of these challenges can motivate people to take action, make informed choices, and advocate for policies that protect mushroom habitats and address environmental issues. Sustainable Harvesting Practices: Education plays a vital role in promoting responsible mushroom harvesting techniques. By teaching proper identification, selective harvesting, and sustainable quantities, individuals can enjoy mushroom foraging while minimizing negative impacts on populations and their habitats. Awareness of sustainable practices ensures the long-term availability of mushrooms for future generations. Medicinal and Economic Potential: Highlighting the medicinal and economic potential of mushrooms raises awareness about their value beyond ecological considerations. Many mushroom species possess medicinal properties and have been used in traditional medicine for centuries. Additionally, mushrooms have economic value in industries such as food, pharmaceuticals, and biotechnology. Recognizing these aspects fosters support for conservation efforts and sustainable management of mushroom resources. Citizen Science and Engagement: Encouraging citizen science initiatives and engagement in mushroom-related activities provides opportunities for learning and involvement. By participating in monitoring programs, workshops, and field trips, individuals can deepen their knowledge, contribute to research, and become advocates for mushroom conservation. Engaging the public in these activities fosters a sense of connection with nature and empowers them to be active participants in conservation efforts. By emphasizing the importance of raising awareness about mushroom ecology and conservation, we can inspire individuals to become stewards of the environment, make sustainable choices, and support initiatives that protect these vital components of our ecosystems. Through education and awareness, we pave the way for a more informed and responsible approach to mushroom conservation and environmental stewardship. Remember to tailor your educational activities to the target audience, keeping the information accessible, engaging, and relevant to their interests and knowledge levels. By employing a variety of educational approaches, you can reach a broader audience and inspire a greater appreciation for mushroom ecology and conservation. By understanding these key points, individuals can contribute to the preservation of mushroom diversity, promote sustainable practices, and help conserve the ecosystems where these remarkable organisms thrive. Biodiversity Preservation: Conserving mushroom species contributes to the preservation of biodiversity. Mushrooms are crucial components of ecosystems, playing essential roles in nutrient cycling, decomposition, and symbiotic relationships. Protecting mushroom diversity ensures the maintenance of healthy and balanced ecosystems. Ecosystem Functioning: Mushrooms are key drivers of ecosystem functioning and stability. They facilitate nutrient recycling, break down organic matter, and contribute to soil fertility. By preserving mushroom populations, we sustain these vital ecological processes, promoting the overall health and resilience of ecosystems. Symbiotic Relationships: Many mushrooms form mycorrhizal associations with plant roots, benefiting both parties. These associations enhance nutrient uptake, improve soil structure, and increase plant resistance to stress. Conserving mushrooms ensures the continuation of these symbiotic relationships, supporting the health and productivity of plants and the overall stability of ecosystems. Climate Change Mitigation: Mushroom conservation plays a role in mitigating climate change impacts. Healthy ecosystems with diverse mushroom populations contribute to carbon sequestration and the regulation of greenhouse gas emissions. By protecting mushroom habitats, we contribute to the broader efforts of climate change adaptation and mitigation. Medicinal and Economic Value: Many mushroom species possess medicinal properties and have been used for centuries in traditional medicine. Conserving mushroom diversity preserves potential sources of new medicines and pharmaceutical compounds. Additionally, mushrooms have economic value in industries such as food, biotechnology, and agriculture, providing livelihoods and economic opportunities for communities. Scientific Discovery and Education: Preserving mushroom diversity allows for ongoing scientific research, species discovery, and educational opportunities. Studying mushrooms enhances our understanding of fungal ecology, genetics, and their broader ecological significance. It also provides educational avenues for people to learn about the fascinating world of fungi and their role in the environment. Conservation Ripple Effects: By protecting mushroom populations and their habitats, we contribute to the conservation of other species and the overall health of ecosystems. Many organisms rely on mushrooms for food, shelter, and other ecological interactions. Conserving mushrooms has positive cascading effects on other organisms and contributes to the preservation of entire ecosystems. In summary, mushroom conservation is crucial for preserving biodiversity, maintaining ecosystem functioning, supporting symbiotic relationships, mitigating climate change, unlocking medicinal and economic potential, promoting scientific discovery, and fostering environmental education. By valuing and protecting mushrooms, we take important steps towards ensuring a sustainable and resilient future for our planet. Learn and Share: Educate yourself about mushroom ecology, conservation, and sustainable practices. Raise awareness about the importance of mushrooms and their conservation. Support Conservation Organizations: Identify and support local or global organizations dedicated to mushroom conservation. Contribute through donations, volunteering, or participating in their programs and initiatives. Your support can help fund research, conservation projects, and educational campaigns. Engage in Citizen Science: Become a citizen scientist and participate in mushroom monitoring programs. Document mushroom sightings, contribute data to research projects, and help scientists better understand the distribution and abundance of mushroom species. Your observations can make a valuable contribution to scientific knowledge. Practice Sustainable Foraging: If you engage in mushroom foraging, do so responsibly and sustainably. Learn about local regulations, obtain necessary permits, and follow ethical harvesting practices. Respect mushroom habitats, only harvest what you need, and leave some behind to ensure future growth and reproduction. Protect Natural Habitats: Support initiatives and policies that prioritize the protection of natural habitats. Advocate for the conservation of forests, wetlands, and other ecosystems that provide suitable conditions for mushroom growth. Join local conservation groups, participate in habitat restoration activities, and voice your concerns about deforestation and habitat destruction. Promote Environmental Stewardship: Take actions to reduce your environmental footprint. Conserve water, reduce waste, and support sustainable land use practices. By adopting environmentally friendly habits, you contribute to the overall health of ecosystems and create a positive impact on mushroom conservation. Engage Others: Inspire friends, family, and your community to get involved in mushroom conservation. Organize workshops, guided walks, or educational events to share your passion for mushrooms and their importance. Encourage others to appreciate and protect these fascinating organisms. Remember, every action, no matter how small, can make a difference. By taking an active role in mushroom conservation, you contribute to the preservation of biodiversity, the health of ecosystems, and the well-being of our planet. Together, we can ensure a sustainable future where mushrooms continue to thrive and play their vital ecological roles! Mushroom Ecology and Conservation Home » Mushroom Ecology and Conservation. Introduction to Mushroom Ecology and Conservation. Significance of Fungi in Ecosystems and their Role in Environmental Sustainability. Importance of Conservation Efforts to Protect Mushroom Species and their Habitats. Not In Stock. Understanding Mushroom Ecology. What Are Mushrooms? These include: Mold: Mold is a type of fungi that often grows on damp surfaces, such as food, walls, or organic matter. Highlight the diversity and abundance of mushroom species. Mushroom Life Cycle. The life cycle of mushrooms encompasses several stages, including spore germination, mycelium growth, and fruiting body formation. Mushroom growth and development are influenced by various factors, including environmental conditions, substrate composition, and genetic factors. Here are some key factors that play a role in mushroom growth:. Ecological Roles of Mushrooms. Mushrooms play vital ecological roles in various ecosystems. Here are some of their key ecological functions:. Mushrooms play significant roles in nutrient cycling, decomposition, and symbiotic relationships with other organisms. Mycorrhizal associations, the symbiotic relationships between fungi such as mushrooms and plant roots, play a significant role in plant health and ecosystem stability. Importance of Mushroom Conservation. Threats to Mushroom Populations. Mushroom species and their habitats face several significant threats that can negatively impact their populations and overall ecosystem health. Here are some major threats:. Deforestation, pollution, climate change, and unsustainable harvesting practices have significant impacts on mushroom species and their habitats. Benefits of Mushroom Conservation. Preserving mushroom biodiversity is of immense value, encompassing ecological, economic, and medicinal benefits. Here are some key aspects of their importance:. Ecological Value: Ecosystem Health: Mushroom biodiversity is crucial for maintaining ecosystem health and functioning. Economic Value: Edible and Culinary Uses: Numerous mushroom species have culinary value and are consumed worldwide. Medicinal Value: Traditional Medicine: Mushrooms have long been used in traditional medicine systems across various cultures. Mushrooms possess diverse applications in agriculture, medicine, and bioremediation due to their unique properties and capabilities. Agriculture: Biocontrol Agents: Certain mushroom species, such as Trichoderma and Tricholoma, have biocontrol properties. Medicine: Medicinal Mushroom Extracts: Many mushroom species contain bioactive compounds with potential therapeutic properties. Bioremediation: Mycoremediation: Certain mushroom species have the ability to degrade or sequester pollutants, making them valuable in bioremediation efforts. Strategies for Mushroom Conservation. Habitat Protection and Restoration. Preserving natural habitats that support mushroom populations is of utmost importance due to the following reasons:. Creating protected areas and implementing habitat restoration initiatives are essential steps in preserving mushroom populations and their natural habitats. Creating Protected Areas: Identify Key Habitats: Conduct thorough assessments to identify key habitats that are rich in mushroom diversity and support critical ecological processes. Implementing Habitat Restoration Initiatives: Assess Habitat Degradation: Conduct thorough assessments of degraded habitats to understand the causes and extent of degradation. Sustainable Harvesting Practices. Sustainable mushroom harvesting involves practices that ensure the long-term viability of mushroom populations and their habitats. The principles of sustainable mushroom harvesting include:. Here are some guidelines to consider:. Citizen Science and Mushroom Monitoring. Citizen science initiatives play a crucial role in mushroom conservation by engaging the public in scientific data collection, monitoring, and research efforts. Here are some ways to promote citizen science initiatives for mushroom conservation:. Citizen scientists play a crucial role in monitoring mushroom populations and contributing to scientific research. Their active participation and contributions provide valuable data that enhances our understanding of mushroom ecology, distribution, and conservation. Here are some key aspects of the role of citizen scientists in monitoring mushroom populations:. Education and Awarenes. Raising awareness about mushroom ecology and conservation is crucial for fostering a deeper understanding of the importance of these fascinating organisms and the need to protect them. Here are key points highlighting the significance of education and awareness:. When it comes to educating the public about mushroom ecology and conservation, various approaches can be effective in conveying information and fostering a deeper understanding. Here are some tips for conducting educational activities:. SureHarvest calculated the overall water footprint per pound of production by collecting information on freshwater applied, precipitation and water embedded in the composting ingredients. The 1. To determine the 1. CO2 equivalent emissions were calculated by tracking total emissions from electricity and fuel used for composting equipment and growing operations e. equipment, heating, cooling, etc. The study calculated the average yield per square foot by measuring more than 42 million square feet of mushroom production area. Each year, growers are able to produce millions of pounds of mushrooms on just a few acres of land. In addition, the soil used to produce mushrooms is made of composted materials. In a second type, the Glomeromycete fungi form vesicular—arbuscular interactions with arbuscular mycorrhiza sometimes called endomycorrhizae. In these mycorrhiza, the fungi form arbuscules that penetrate root cells and are the site of the metabolic exchanges between the fungus and the host plant Figure 5 and Figure 6. The arbuscules from the Latin for little trees have a shrub-like appearance. Orchids rely on a third type of mycorrhiza. Orchids are epiphytes that form small seeds without much storage to sustain germination and growth. Their seeds will not germinate without a mycorrhizal partner usually a Basidiomycete. After nutrients in the seed are depleted, fungal symbionts support the growth of the orchid by providing necessary carbohydrates and minerals. Some orchids continue to be mycorrhizal throughout their lifecycle. Figure 6. The a infection of Pinus radiata Monterey pine roots by the hyphae of Amanita muscaria fly amanita causes the pine tree to produce many small, branched rootlets. The Amanita hyphae cover these small roots with a white mantle. b Spores round bodies and hyphae thread-like structures are evident in this light micrograph of an arbuscular mycorrhiza between a fungus and the root of a corn plant. credit a: modification of work by Randy Molina, USDA; credit b: modification of work by Sara Wright, USDA-ARS; scale-bar data from Matt Russell. If symbiotic fungi are absent from the soil, what impact do you think this would have on plant growth? Other examples of fungus—plant mutualism include the endophytes: fungi that live inside tissue without damaging the host plant. Endophytes release toxins that repel herbivores, or confer resistance to environmental stress factors, such as infection by microorganisms, drought, or heavy metals in soil. Mycorrhizae are the mutually beneficial symbiotic association between roots of vascular plants and fungi. A well-accepted theory proposes that fungi were instrumental in the evolution of the root system in plants and contributed to the success of Angiosperms. The bryophytes mosses and liverworts , which are considered the most primitive plants and the first to survive on dry land, do not have a true root system; some have vesicular—arbuscular mycorrhizae and some do not. They depend on a simple rhizoid an underground organ and cannot survive in dry areas. True roots appeared in vascular plants. Vascular plants that developed a system of thin extensions from the rhizoids found in mosses are thought to have had a selective advantage because they had a greater surface area of contact with the fungal partners than the mosses and liverworts, thus availing themselves of more nutrients in the ground. Fossil records indicate that fungi preceded plants on dry land. The first association between fungi and photosynthetic organisms on land involved moss-like plants and endophytes. These early associations developed before roots appeared in plants. The fungi involved in mycorrhizae display many characteristics of primitive fungi; they produce simple spores, show little diversification, do not have a sexual reproductive cycle, and cannot live outside of a mycorrhizal association. The plants benefited from the association because mycorrhizae allowed them to move into new habitats because of increased uptake of nutrients, and this gave them a selective advantage over plants that did not establish symbiotic relationships. Lichens display a range of colors and textures Figure 7 and can survive in the most unusual and hostile habitats. They cover rocks, gravestones, tree bark, and the ground in the tundra where plant roots cannot penetrate. Lichens can survive extended periods of drought, when they become completely desiccated, and then rapidly become active once water is available again. Figure 7. Lichens have many forms. They may be a crust-like, b hair-like, or c leaf-like. Figure 8. This cross-section of a lichen thallus shows the a upper cortex of fungal hyphae, which provides protection; the b algal zone where photosynthesis occurs, the c medulla of fungal hyphae, and the d lower cortex, which also provides protection and may have e rhizines to anchor the thallus to the substrate. Lichens are not a single organism, but rather an example of a mutualism, in which a fungus usually a member of the Ascomycota or Basidiomycota phyla lives in close contact with a photosynthetic organism a eukaryotic alga or a prokaryotic cyanobacterium Figure 8. Generally, neither the fungus nor the photosynthetic organism can survive alone outside of the symbiotic relationship. The body of a lichen, referred to as a thallus, is formed of hyphae wrapped around the photosynthetic partner. The photosynthetic organism provides carbon and energy in the form of carbohydrates. Some cyanobacteria fix nitrogen from the atmosphere, contributing nitrogenous compounds to the association. In return, the fungus supplies minerals and protection from dryness and excessive light by encasing the algae in its mycelium. The fungus also attaches the symbiotic organism to the substrate. The thallus of lichens grows very slowly, expanding its diameter a few millimeters per year. Both the fungus and the alga participate in the formation of dispersal units for reproduction. Lichens produce soredia , clusters of algal cells surrounded by mycelia. Soredia are dispersed by wind and water and form new lichens. Lichens are extremely sensitive to air pollution, especially to abnormal levels of nitrogen and sulfur. The U. Forest Service and National Park Service can monitor air quality by measuring the relative abundance and health of the lichen population in an area. Lichens fulfill many ecological roles. Caribou and reindeer eat lichens, and they provide cover for small invertebrates that hide in the mycelium. In the production of textiles, weavers used lichens to dye wool for many centuries until the advent of synthetic dyes. Figure 9. A leaf cutting ant transports a leaf that will feed a farmed fungus. credit: Scott Bauer, USDA-ARS. Fungi have evolved mutualisms with numerous insects in Phylum Arthropoda: jointed, legged invertebrates. |
| Mushrooms | Farmscape Ecology Program | Ecological Role: Mushrooms are Mushroom Ecology Study in ecosystems as decomposers and symbiotic Srudy. Sustainable Edology Practices: Eccology mushrooms that are collected Mushroom Ecology Study culinary or Ecologg Mushroom Ecology Study, adopting sustainable harvesting practices is crucial. Search all BMC articles Search. Open Access This article is licensed under a Creative Commons Attribution 4. Using regional field guides helps narrow down possibilities. Respect for Ecosystems: Recognize that mushrooms are an integral part of ecosystems, playing important roles in nutrient cycling, decomposition, and symbiotic relationships. |
| The Ecology of Morel Mushrooms: A Fascinating Study | In fact, many mushrooms rank above vegetables , and it comes to their protein content. Besides the benefits of fungi for the environment, they also provide health benefits for humans. In fact, six percent of edible mushrooms possess medicinal properties, which can help prevent diseases and boost our immune system. Shiitake, for example, present antiviral properties and can reduce serum cholesterol. Other species are known to possess a number of other benefits such as inhibit tumor and the development of AIDS, anti-oxidative property and antidiabetic effect. Fungi have been found to help degrade various pollutants from the environment, such as plastic and other petroleum-based products , pharmaceuticals and personal care products , and oil. Some of these substances are persistent toxins, which mean that they take a long time to break down in the environment and accumulate in humans and other species, presenting adverse effects on organisms. Therefore, fungi can act as a powerful tool to reduce environmental pollution. In addition, studies show that some fungi species can help in ecosystem restoration by advancing reforestation in degraded soils and act as pest control seeing that some species are pathogens of arthropods or nematodes. Mycelium, which is the root structure of mushrooms are now being used to replace unsustainable materials, such as plastic, synthetic and animal-based products. The products from Mycelium are biodegradable and require less water and land resources to be produced. Some of the mycelium-based products already in the market include packaging, clothes, shoes, sustainable leather, skincare products and others. Numerous factors can jeopardize soil fungi diversity and functioning, including deforestation, land conversion to agriculture, soil degradation and salinization. Therefore, sustainable soil management and ecosystem conservation is essential in preserving fungi diversity and enhancing the benefits of its ecosystem services for human and nature. This article was originally published here. Ecosystem Restoration What is Ecosystem Restoration? Explore Scientific Launch Report Types of Ecosystem Restoration About the UN Decade Background Strategy World Restoration Flagships Generation Restoration Cities Documentary Series Frequently Asked Questions Partners Our Partners Advisory Board Task Forces Restoration Implementers Latest Events News Newsletters Podcast Get Involved Nominate World Restoration Flagship Learn to restore Play a game, score for nature Take Action for Lakes Resources Communication Materials Publications Videos. Image by: Chloride free. Benefits of fungi Fungi are an important part of soil biodiversity , and this diverse group of organisms can help tackle global challenges, including climate change and hunger. Nutrient Cycling Fungi have the ability to transform nutrients in a way that makes them available for plants. Carbon Cycling and Climate regulation Fungi are important contributors to the soil carbon stock. Nutrition and food security Some mushrooms are commonly found in the diets of many people around the world. Human Health Besides the benefits of fungi for the environment, they also provide health benefits for humans. Environmental protection Fungi have been found to help degrade various pollutants from the environment, such as plastic and other petroleum-based products , pharmaceuticals and personal care products , and oil. We performed all-versus-all blast using mpiBLAST 1. Next, we screened for gene families that contained a single representative gene for each species, or ones that contained inparalogs but no deep paralogs. Deep paralogs were identified following Nagy et al. Gene trees were inferred using the PTHREADS version of RAxML 8. A single inparalog, closest to the root on the basis of root-to-tip patristic distances was retained for each species. We used RAxML 8. We ran bootstrap replicates using the rapid hill-climbing algorithm. Because in initial analyses Peniophora sp. Altogether, 1, in gene families protein sequences were excluded from the analyses. The robustness of the dataset was tested by eliminating incrementally higher numbers of fast-evolving sites using six levels of stringency in Gblocks b Using these parameters, we eliminated 8. We performed maximum-likelihood phylogenetic inference for each of the reduced datasets in RAxML as described above. Maximum-likelihood trees for the 5,taxon dataset were inferred using the parallel version of RAxML v. The phylogenomic tree was used as a backbone monophyly constraint. We performed maximum-likelihood inferences and tested whether these trees adequately represented the plausible set of topologies given the alignment. This was done to ensure that phylogenetic uncertainty is properly taken into account in subsequent comparative analyses. If our tree set contains all plausible topologies, then the rolling average of pairwise Robinson—Foulds distances should show a saturation as a function of increasing the number of trees. We then plotted the rolling average, maximum and minimum values as a function of the number of trees in R. Due to computational limitations, we focused on ten maximum-likelihood trees that maximize topological diversity as inferred on the basis of Robinson—Foulds distances as representative trees for molecular clock analysis. The ten maximum-likelihood trees for subsequent analyses were chosen evenly from the resulting clusters of trees. To overcome the computational limitations of inferring accurate chronograms for thousand-tip phylogenies, we adopted a two-step strategy. First, PhyloBayes 4. Then we used the ages and parameters estimated in PhyloBayes as input parameters for FastDate development version 61 provided by T. Flouri for analysing the complete 5,species dataset. A uniformly distributed prior was applied to fossil calibration times. All analyses were run until convergence, typically 15, cycles. Convergence of chains was assessed by visually inspecting the likelihood values of the trees and the tree height parameter. We sampled every tree from the posterior and after discarding the first 7, samples as burn-in we summarized the posterior estimates using the readdiv function of PhyloBayes. Next, we used FastDate, a program that implements the speed dating algorithm described in Akerborg et al. FastDate analyses were run with time discretized into 1, intervals and the ratio of sampled extant individuals set to 0. The extensive sampling density of our tree allowed us to use more fossil calibration points than any study before and to place them more precisely within the tree. Eight fossils were used as calibration points Supplementary Table 2 for the crown node of the specified taxa. We excluded a number of prospective well-preserved fossils for reasons of redundantly calibrating an already calibrated node Appianoporites vancouverensis —Hymenochaetales 62 , Protomycena electra —marasmioid clade 63 , Cyathus dominicanus— Nidulariaceae 64 , Fomes idahoensis —Polyporales Geastrum tepexensis 66 was not considered as it could be assigned to either of the two earth-star clades, one in the Phallomycetidae Geastraceae or the other in the Boletales Astraeus. For other mushroom fossils, the taxonomic affiliations were deemed too uncertain. To investigate if there is any conflict between the fossil calibration points we conducted a fossil cross-validation analysis following Near et al. This resulted in eight independent molecular dating analyses. To quantify conflict between single fossil calibrations, first we calculated the sum of the square differences between molecular age estimates and fossil ages:. where x is the fossil calibration point used and D i is the difference between molecular age estimate and fossil age for fossil i. We ordered the SS values of each of the eight analyses in descending order and calculated the average squared deviation for all fossil calibrations:. Next, the analysis with the highest SS value was removed and s was recalculated. We continued this process until only two analyses remained. In parallel, we performed one-tailed F -tests to check whether the removal of the fossil had a significant effect on the variance of s. The principle of this procedure is that during the stepwise removal of fossils, s should decrease by small constant values and variance should not decrease significantly. We examined the robustness of our molecular age estimates using phylogenomic methods as an alternative to the 5, species phylogeny. Specifically, we tested whether the differences between our and previous 17 , 18 molecular clock estimates for Agaricomycete orders were attributable to differences in the dataset or analytical method used or a difference in how precisely fossils could be placed on the tree. To this end, we performed a series of molecular clock analyses on our phylogenomic dataset that resembled that of Kohler and Floudas in terms of topology and taxon sampling density, but differed in the placement of some fossil calibrations. A key difference was that our phylogenomic tree included the most recent common ancestor MRCA of the Hymenochaetales and that of the Suillaceae, which allowed us to calibrate the MRCA of these clades, as opposed to their stem nodes by Kohler et al. We used a smaller, more conserved subset of the gene and species phylogenomic dataset which was computationally not tractable in these analyses. First, we selected the first 70 most conserved genes of the gene dataset by calculating the mean genetic distances for each gene using the dist. alignment function of the seqinR R package v. To enable a more accurate placement of fossil calibration points we added additional three species Cyathus striatus , Pycnoporus cinnabarinus , Suillus brevipes to this dataset Supplementary Table 1 and excluded two taxa that harboured ambiguous positions. We searched homologous sequences in the additional genomes using blastp v. We selected the best hit smallest E -value as a one-to-one ortholog if the second best hit had a significantly worse E -value by 20 orders of magnitude. Protein clusters were aligned by PRANK v. Next, conserved blocks of the alignments were selected using Gblocks v. A phylogenomic tree was constructed by RAxML v. To dissect sources of differences in molecular age estimates, we ran analyses under three fossil calibration schemes Supplementary Data 2 and the species phylogenomic tree. Next, we replicated the analyses of Kohler et al. Finally, we used the calibrations used by Kohler et al. scheme 2 but placed the two fossils in the MRCAs of the Suillaceae and marasmioid clade, respectively Kohler et al. We ran a series of molecular clock analyses in r8s v. The additive penalty function was applied and the optimization was run 25 times starting from independent starting points. In one optimization step, after reaching an initial solution, the solution was perturbed and the truncated Newton optimization was rerun 20 times. We compared the results of previous studies to that of analyses across seven ancestral nodes in Agaricomycotina Supplementary Data 2. We used the mcmctree method implemented in PAML v. The independent-rates clock model, a WAG substitution model and approximate likelihood calculation 72 were used. The birth rate, the death rate and the sampling fraction of the birth-death process were set to 1, 1 and 0. The shape and the concentration parameter of the gamma-Dirichlet prior for the drift rate coefficient σ 2 was set to 1 and three different scale parameters were tested 10, , 1, to see their effect on the time estimates. The substitution rates of each gene were estimated by codeml under a global clock model, to set the parameters of the gamma-Dirichlet prior for the overall rate. By calculating the mean substitution rate of the loci and examining the density plot of the rates we set up a prior that reasonably fitted the data: the shape parameter, the scale parameter and the concentration parameter were set to 5, MCMC analysis was run for 80, iterations, discarding the first 20, iterations as a burn-in and sampling every 30th tree from the posterior. After three independent analyses were run the convergence of log-likelihood values was visually inspected and the estimated ages were compared between replicates. We discretely coded three characters, the presence of a cap, fruiting body type and substrate preference for the 5, species. Fruiting body types were coded as one of six types and data were compiled from the literature. Transitional morphologies, or species for which no clear decision could be made on fruiting body type were coded as uncertain. Resupinate fruiting bodies were defined as crust-like or effused, flat morphologies that follow the morphology of the substrate, but irrespective of thickness or hymenophore type. The agaricoid type was defined as having a distinguishable stipe and cap. Cyphelloid species were coded following Bodensteiner The gasteroid types included species with closed fruiting bodies that produce spores internally. No distinction was made between secotioid, sequestrate and false-truffle morphologies and all were coded as gasteroid. The presence of a cap, that is pileate-stipitate morphology, was coded on the basis of literature data as either absent state 0 or present state 1. Species with rudimentary or reduced caps were coded as uncertain. On the other hand, species having records on both gymno- and angiosperm substrates, described in the literature as generalists or given multiple gymno- or angiosperm substrate plant species were coded as generalists. Species with insufficient data or no data at all were treated as missing data. Soil-inhabiting saprotrophs were coded on the basis of their association with either gymno- or angiosperms, if a clear preference was reported in the literature. We downloaded 5,, fungal GPS records from the GBIF database, representing 4, Agaricomycetidae species. In cases where only the province, country or biogeographic realm was available, we took the centroid of the area as a proxy for GPS location. All GPS data were handled and processed in R Noise was added to identical GPS coordinates using the jitter function in R. State-dependent diversification rates were estimated in two ways: 1 using centroid latitudes as continuous traits for example, Sánchez-Ramírez et al. We used the data mentioned above to first calculate a centroid coordinate RGEOS R package in cases where multiple GPS records exist per species. Then we took the centroid latitude for each species. For singletons, we simply took the latitude of each record. We also used the GPS database to calculate a standard deviation for latitude per species. For species with a single record, we took the mean standard deviation of species with multiple records. We fitted multiple Quantitative State Speciation and Extinction QuaSSE 76 models, using a maximum-likelihood approach, to ten of the 5,species chronograms. Models included speciation rate changes as a constant function of the trait no effect , as a linear function or as a Gaussian function, keeping the extinction rate constant We also added two models in which the extinction rate varied as linear or Gaussian functions, while speciation rate remained constant. Akaike information criterion values were averaged across phylogenies and compared between different models. Free vector and raster map data are available at www. To obtain discrete areas, first we divided all terrestrial WWF ecoregions into either tropical or extra-tropical. For tropical areas we considered: Tropical and Subtropical Moist Broadleaf Forests, Tropical and Subtropical Dry Broadleaf Forests, Tropical and Subtropical Grasslands, Savannas and Shrublands. All other terrestrial ecoregions were deemed extra-tropical. Ecoregion polygons were integrated that is, dissolved in a way that only two-state areas were found Supplementary Note 7. For species with multiple GPS records, we extracted binary information about their presence in both areas. For records that were not found precisely within the geometry of the area, we took the area to which the distance to the GPS point was closer. Using these three states for each taxon, we fitted multiple constrained models and one full model of Geographic State Speciation and Extinction GeoSSE 77 in a maximum-likelihood framework. The full model consisted of seven parameters: 1 speciation rate in the tropics, 2 speciation rate in the extra-tropical zone, 3 the allopatric speciation rate speciation rate in both tropical and extra-tropical regions , 4 extinction rate in the tropics, 5 extinction rate in the extra-tropical zone, and dispersal rates to 6 the tropics and to 7 the extra-tropical zone. The constrained models consisted of: 1 speciation in the tropics is equal to speciation in the extra-tropical zone; 2 extinction in the tropics is equal to extinction in the extra-tropical zone and 3 dispersal to the tropics occurs at the same rate as dispersal to the extra-tropical zone. In each case, a single parameter for speciation, extinction, and dispersal was respectively estimated, allowing the other parameters of the model to vary. To explore the parameter space better, we re-estimated parameters using MCMC on the full model. In a similar way as above, we used Akaike information criterion scores to rank the models. The BiSSE model 38 was used in diversitree. Each of the constrained models were compared to the best fit model on the basis of log-likelihood values maximum-likelihood analyses in BayesTraits , log-Bayes factors MCMC analyses in BayesTraits or LRT and Akaike information criterion scores maximum-likelihood analyses of BiSSE model in diversitree 38 , 39 , 78 , In BayesTraits, a difference of 2. BayesTraits analyses maximum likelihood and MCMC were performed on phylogenetic trees using the MultiState module of the program. Before the final MCMC analyses, we tried several prior distributions uniform, exponential, gamma and the hyper-prior versions of these with different settings. On the basis of preliminary analyses, we found that the gamma distribution was most optimal, therefore in further analyses we used a gamma hyper-prior with different prior distributions for each parameter Supplementary Note 5. All preliminary BayesTraits analyses were conducted with the following settings: 1,, generations, 10, generations as burn-in and sampling every th generation. We forced Markov chains to spend , generations on each tree using the equaltree option, with , generations as burn-in and sampling every th generation. The marginal likelihood was estimated by the stepping stone method 78 , 80 using 50 stones with a chain length of 5, All analyses in BayesTraits were repeated three times to check the congruence of independent runs. We used ten chronograms to analyse trait-dependent diversification under the BiSSE model implemented in the R package diversitree v. Maximum-likelihood search started from the point in the parameter space determined by the function starting. State-specific sampling fractions were defined on the basis of data from Species Fungorum 44 see Accounting for random and incomplete taxon sampling. The convergence of the chains was visually checked on the basis of likelihood and parameter values. We reconstructed the ancestral states using stochastic character mapping as implemented in phytools v. This method is a modified version of a previously published algorithm 82 , which samples discrete character histories from the posterior probability distribution. We performed the analysis with the make. simmap function on ten time-calibrated trees under a Markov model with all rates different. The stochastic character histories were simulated 5, times. We plotted state posterior probabilities through time using a custom R script. Briefly, we summarized character-state posterior probabilities through the time scale of our ten chronograms split into bins. Ancestral probability distributions of substrate preference for the MRCAs of each of the orders and some additional clades were plotted as pie charts using the nodelabels function of ape v. To meet the assumption of random or complete sampling of the BAMM and BiSSE models 20 , 39 , we specified the sampling fraction of each genus in accordance with the described number of species based on Species Fungorum To gather information on described species, we screened all orders of the Agaricomycetes, Dacrymycetes and Tremellomycetes in Species Fungorum and gathered all species with a custom java program available from the authors on request. We took into account taxonomic and nomenclatural synonymy if indicated by Species Fungorum. We accounted for incomplete taxon sampling by two strategies. First, we assigned specific sampling fractions to the character states BiSSE model or to genera BAMM model. In these cases we used the built-in correction of the BiSSE and BAMM models 20 , 85 to account for missing species in our phylogeny. Second, because we could have unintentionally oversampled certain genera for example, because of better availability of specimens , we statistically tested for oversampling and generated a pruned phylogeny in which each genus is represented in proportion of its described diversity. We adjusted taxon sampling in our phylogeny by iteratively deleting species from genera that were oversampled relative to the mean sampling fraction of the tree, until sampling fractions of each genera corresponded their known size as judged by a comparison to Species Fungorum. We performed analyses under the BiSSE model to examine the effect of agaricoid fruiting body type on diversification rate. BiSSE analyses were carried out in diversitree v. We performed model tests to examine if the presence of a cap influenced speciation and extinction rates. Models were compared by LRT in R. We used BAMM v. We analysed ten chronograms and ran MCMC analyses for million generations using four independent chains per analysis with 50 million generations as burn-in. Prior parameters were optimized using the setBAMMpriors function in BAMMtools v. We accounted for incomplete taxon sampling as described above. To ensure that a shift is highly supported by the data and the prior had negligible contribution, we examined only core shifts; that is, those with a prior-to-posterior marginal odds ratio exceeding 5 ref. We compared core shifts across ten chronograms to obtain a consensus view on shifts that can be detected in all or most of the trees. To this end, we first empirically identified taxonomically similar clades for which a core shift was inferred, taking into account topological differences among trees. Then we noted whether the mean diversification rate change after the shift is positive or negative that is, rate acceleration or deceleration. There were cases when several core shifts were inferred on adjacent branches around the MRCA of a given clade. These come from distinct shift configurations sampled during the MCMC analysis and correspond to the same signal of rate variation in the data but were located to adjacent branches of the tree. In such cases, we chose the shift with the highest posterior probability, noting that the biological reality of increasing rates might be spread out across a few adjacent branches around the one with the highest posterior. For this, we calculated the posterior probability of each core shift at each generation, as if the analysis was stopped at that point and plotted posterior probabilities as a function of generation using the ggplot2 v. We also took into account the distinct shift configurations by examining whether a rate increase, after a congruent core shift was explained by a rate decrease after another core shift. First, we determined congruent core shift—core shift pairs that could potentially be mutually exclusive to each other. These shift pairs were determined in one tree, usually in the tree where a congruent core shift had high posterior probability. Then we calculated two kinds of posterior proportions: one for co-occurring shift pairs and one for each of the single occurrence of the shifts. We said that two shifts were mutually exclusive to each other if only a negligible co-occurrence was presented and the direction of the diversification rate change was different between the single occurrence posterior samples. To reveal tree-wide evolutionary patterns we calculated average net rates through time using the getRateThroughTimeMatrix function and plotted by the plotRateThroughTime function of the BAMM package. There have been critics of the BAMM method recently 90 , Meyer and Wiens 91 found that the method-of-moments estimator yielded stronger relationship between true and estimated diversification rates than BAMM, particularly in smaller clades. Therefore, to validate the BAMM results we used the method-of-moments estimator on clades with congruent core shifts. We used the bd. ms function in geiger 2. The analyses were performed on all the 85 clades with congruent core shifts, using three different relative extinction fractions 0, 0. We calculated unsampled species fractions using the genus-specific sampling fractions we determined for BAMM analyses. For the same set of clades we calculated average net diversification and net speciation rates from BAMM data using the getCladeRates function. Then we performed linear regressions between method-of-moments estimates with different settings and average net diversification or net speciation rates from BAMM. We examined the adjusted r 2 and the P values of the models to evaluate the correspondence between the two methods. We performed analyses using the compound Poisson process on mass extinction times model CoMET 27 , 94 , to examine tree-wide variation in diversification rate and occurrence of mass extinctions during the evolution of mushroom-forming fungi. First, we conducted a model comparison on ten chronograms using the CoMET model with a constant rate birth-death process implemented in the TESS 2. R package We compared models with and without mass extinction events on the basis of marginal likelihoods. We allowed the occurrence of a mass extinction event along the entire time span of a tree and we set the survival probability of species to 0. The overall sampling fraction of species was set to 0. MCMC analyses were run for 20, generations and the first 2, posterior samples were discarded as a burn-in. Marginal likelihoods were estimated using stepping stone simulation using stepping stones. Then, we performed reversible jump Markov chain Monte Carlo rjMCMC analyses under the CoMET model to sample from the space of episodically varying birth-death processes with mass extinction events. In this analysis, we also tested the significance of the occurrence of a mass extinction event by performing model tests within time intervals. We examined the sensitivity of the posterior probabilities to different prior settings in preliminary analyses of a randomly chosen tree. We examined models with two or ten expected mass extinction events, with 30, or expected rate changes and with survival probabilities of 0. All of these preliminary analyses were run for 1. We used a log-normal prior on speciation and extinction rates with a mean of 0. In the final analyses we used all ten chronograms and an empirical hyper-prior on rate parameters on the basis of , iterations with , burn-in. The priors on the number of expected mass extinction and the expected rate changes were set to 2 and 30, respectively, on the basis of results of preliminary analyses. We set the survival probability to 0. Analyses were run for 3 million generations with 1 million generations as burn-in. The convergence of the analyses was checked by visually inspecting the log-likelihood values and by computing the effective sample size and the Geweke diagnostic for the log-likelihoods, the number of speciation rate shifts, the number of extinction rate shifts and the number of mass extinction events using the effectiveSize and the geweke. diag function of the CODA 0. To check the convergence of interval-specific parameters we used the tess. diagnostics function of the TESS package. 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