Predicting edible mushroom productivity using forest carbon allocation modeling and immunoassays of ectomycorrhizae

Remote Sensing

Evaluating commercial mushroom crops and their values at the scale of landscapes would enable planners or policy analysts to anticipate how regional mushroom crops might be influenced by changes in climate, pollution, exotic forest pests, forest age class distributions, timber management regimes, or land-use patterns. As previously mentioned, the 3PG model has been linked to satellite imagery of canopy photosynthetic capacity to predict forest growth across landscapes (Coops et al. 1998). Satellite sensing of canopy conditions for scaling the 3PG model to landscape estimates of mushroom productivity will be ineffective, however, unless we better understand the range and habitat preferences of the modeled mushroom species. After the core modeling research is underway, we plan to survey mushroom experts (mycology club members, agency botanists, and commercial mushroom harvesters) about the habitat preferences of commercially harvested mushroom species. By incorporating summaries of this habitat information into geographic information system (GIS) databases, we will be able to select appropriate habitat strata for application of remotely sensed canopy data. This approach will allow us to calculate mushroom productivity and crop values at watershed, landscape, or regional scales.

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