Predicted Fungal Habitat Suitaibility Across Los Angeles County



Introduction.

Fungi are a diverse kingdom of organisms that play essential roles in ecosystem functioning through decomposition, nutrient cycling, and forming symbiotic relationships with plants. Due to their remarkable diversity, fungi have historically been difficult to classify, leading to centuries of debate among biologists and mycologists (Blackwell, 2011). Today, fungi are recognized as a distinct kingdom identified by: distribution, vegetative state, cell wall, life cycle, nutrition, spores, sporocarps, ecology, nuclear status, and habitat (Webster & Weber, 2007). Fungi are commonly associated with terrestrial and freshwater habitats, although some species are adapted to saline and marine environments (Webster & Weber, 2007). The occurrence of fungi is strongly influenced by environmental conditions, as different species require specific habitat characteristics to grow and reproduce. Fungal occurrence is also highly seasonal within each habitat due to shifts in temperature, precipitation, and moisture availability, which affect the timing and abundance of fungal fruiting.

Abiotic gradients can affect fungal communities by acting as environmental filters. Mohamed and Martiny (2011) found that salinity gradients significantly altered fungal community composition across estuarine environments, suggesting that environmental conditions can determine which fungal taxa are able to occupy specific habitats. Although salinity had a weaker influence on overall fungal diversity compared with plant presence, it affected fungal community structure by favoring different groups under different environmental conditions. This suggests that environmental conditions determine which fungal taxa are able to occupy specific habitats. Likewise, climatic variables, such as precipitation and temperature, influence the timing and geographic distribution of fungal fruiting. Changes in these environmental conditions can shift fruiting seasons as well as available suitable habitats (Boddy et al., 2014). Fungal distribution is shaped by multiple environmental conditions instead of a single variable.

Los Angeles County contains a wide range of environmental conditions, including highly developed urban areas, coastal environments, forests, mountainous regions, and chaparral. These landscapes have variations in temperatures, elevation, vegetation, precipitation, and soil conditions that may influence fungal habitat suitability. Although Los Angeles County contains diverse ecosystems that may support their own fungal communities, fungal research in this region has received less attention compared to other parts of the United States. However, there are citizen science platforms, such as iNaturalist, that provide a growing source of information and georeferenced fungal observations that can be used to examine fungal distribution patterns.

Data Collection.

Fungal occurrence data were collected from iNaturalist, a citizen science platform where global users submit georeferenced observations of organisms. The dataset was filtered to include fungal observations within Los Angeles County that contained geographic coordinates, observation dates, and available taxonomic identification. Lichens were not included in the dataset, only fungi. Records collected between 2016 and 2026 were included to represent recent documented fungal occurrences within the study area. The filtered observations were then imported as point features to visualize the spatial distribution of documented fungi across Los Angeles County and compare observed locations with predicted habitat suitability.

Environmental datasets are from public available sources, including the USDA Forest Service, PRISM Climate Group, United States Geological Survey (USGS), and the National Land Cover Database (NLCD). Environmental variables used in the suitability model are: land cover, tree canopy cover, precipitation, temperature, elevation, and slope. These datasets were chosen to represent important ecological factors that influence fungal habitat conditions. Table 1 summarizes the environmental variables used in the fungal habitat suitability model.

Tables (2)

Spatial Analysis.

Environmental raster datasets were prepared and analyzed to develop a fungal habitat suitability model for Los Angeles County. All datasets were standardized to the same coordinate system, NAD 1983 StatePlane California V FIPS 0405 (US Feet) in order to maintain consistency during analysis. Each environmental variable was reclassified into five suitability categories ranging from 1 (lowest suitability) to 5 (highest suitability). The reclassification process converted categorical land cover data and environmental measurements into standardized suitability values combined within a raster model. Suitability scores were calculated and assigned based on ecological relationships between each environmental factor and habitat conditions for fungi. A weighted raster overlay approach was used to combine environmental variables into a final habitat suitability model. Temperature, elevation, and slope were assigned lower weights based on their influence; whereas, land cover, tree canopy cover, and precipitation were assigned higher weights. These weighted values are summarized in Table 2. The Raster Calculator tool was used to create the final suitability raster by combining the weighted environmental layers. Higher output values represent areas where multiple environmental conditions align with favorable characteristics. The final suitability model was then compared with iNaturalist fungal observations to evaluate whether predicted suitable habitats aligned with documented fungi occurrences across the county.

Results

The predicted fungal habitat suitability model identified differences in environmental conditions across the county. Areas with higher suitability values were located in vegetated and mountainous regions, while lower suitability were associated with developed urban areas. The final suitability model showed that areas with combined favorable conditions received higher suitability scores. Particularly, regions with greater vegetation cover, suitable temperature, high vegetation, and increased precipitation were identified as areas with greater predicted potential for fungal habitats. When comparing the predicted habitat suitability and iNaturalist fungal observations, a lot of the fungi documented concentrated in urban areas rather than mountainous regions. In other words, the most fungi sightings are in the lowest suitability class.

Tree canopy cover was one of the environmental variables included in the habitat suitability model. Higher canopy coverage was concentrated in mountainous regions. Lower canopy coverage occurred in mainly urbanized areas. The distribution of tree canopy cover corresponds with areas identified as higher suitability, exhibiting the importance of vegetation when predicting fungal habitat conditions.

References.

Blackwell, M. (2011). The Fungi: 1, 2, 3… 5.1 million species?. American Journal of
Botany, 98(3), 426-438.

Boddy, L., Büntgen, U., Egli, S., Gange, A. C., Heegaard, E., Kirk, P. M., ... & Kauserud,

H. (2014). Climate variation effects on fungal fruiting. Fungal Ecology, 10, 20-33.

iNatualist (n.d.). iNaturalist observations. https://www.inaturalist.org

Mohamed, D. J., & Martiny, J. B. (2011). Patterns of fungal diversity and composition
along a salinity gradient. The ISME journal, 5(3), 379-388.

National Land Cover Database. (n.d.). National Land Cover Database (NLCD). U.S.
Geological Survey. https://www.mrlc.gov

PRISM Climate Group. (n.d.). PRISM climate data. Oregon State University.
https://prism.oregonstate.edu.

U.S. Department of Agriculture Forest Service. (n.d.). Tree Canopy Cover dataset.

U.S. Geological Survey. (n.d.). 3D Elevation Program (3DEP) Digital Elevation Model.

Webster, J., & Weber, R. (2007). Introduction to fungi. Cambridge University Press.

Back to Index

Norah Lee

(1) Archives

(2) Drawings

(3) Cartography

(4) Writing

gallery

Cv

⁽¹⁾Archives

⁽²⁾Drawings

⁽³⁾Cartography

⁽⁴⁾Writing