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. 2008 Mar 11;105(10):3811-4.
doi: 10.1073/pnas.0709037105. Epub 2008 Feb 29.

Mushroom fruiting and climate change

Affiliations

Mushroom fruiting and climate change

Håvard Kauserud et al. Proc Natl Acad Sci U S A. .

Abstract

Many species of fungi produce ephemeral autumnal fruiting bodies to spread and multiply. Despite their attraction for mushroom pickers and their economic importance, little is known about the phenology of fruiting bodies. Using approximately 34,500 dated herbarium records we analyzed changes in the autumnal fruiting date of mushrooms in Norway over the period 1940-2006. We show that the time of fruiting has changed considerably over this time period, with an average delay in fruiting since 1980 of 12.9 days. The changes differ strongly between species and groups of species. Early-fruiting species have experienced a stronger delay than late fruiters, resulting in a more compressed fruiting season. There is also a geographic trend of earlier fruiting in the northern and more continental parts of Norway than in more southern and oceanic parts. Incorporating monthly precipitation and temperature variables into the analyses provides indications that increasing temperatures during autumn and winter months bring about significant delay of fruiting both in the same year and in the subsequent year. The recent changes in autumnal mushroom phenology coincide with the extension of the growing season caused by global climate change and are likely to continue under the current climate change scenario.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Temporal variation in fruiting during the period 1940–2006. (A) Diagram showing temporal changes in seasonal fruiting time during the period 1940–2006. Lines indicate fitted year effect with 95% bootstrap confidence limits from a GAM in which species and location effects were accounted for. The trend was modeled as a smooth effect of time and was significantly positive (P < 0.001, bootstrap test). Points indicate partial residuals averaged for each species and year combination. (B) Changes in fruiting during the period 1940–2006, partitioned on early (red; 28 species), middle, (black; 27 species) and late (blue; 28 species) fruiters. Lines indicate fitted year effects with 95% bootstrap confidence limits (for the median of the initial mean fruiting dates within each group) from a GAM in which species and location effects were accounted for. The trend was modeled as a tensor-product smooth function of time and initial fruiting day. This model provided significantly better fit to the data than the model with a common trend for all species (P < 0.001, bootstrap test). Points indicate partial residuals averaged for each species and year combination. (C) Displacement in fruiting time during the period 1940–2006 for the 83 fungal taxa related to initial (1940–1959) mean day of fruiting of each species. Displacement in fruiting (per 60 years) was calculated for each species separately by using GAMs with linear time effects and the geographic effects accounted for by smooth functions of longitude and latitude (thin-plate regression spline with maximally 11° of freedom). Filled points indicate statistically significant effects (P < 0.05, bootstrap tests for each species). Lines indicate linear regression line ± 1.96 standard error (across species). (D) Residuals from the model shown in B. Lines indicate quantiles (5%, 10%, 25%, 50%, 75%, 90%, and 95%) as estimated by quantile regression (23, 24). The standard deviations of the residuals within years were negatively correlated with year (Pearson's correlation coefficient, r = −0.46, 95% bootstrap c.i. = −0.64, −0.26), as were the standard deviations of the raw observations (r = −0.47, c.i. = −0.63, −0.28).
Fig. 2.
Fig. 2.
Spatial patterns in mean day of fruiting of 83 fungal species in Norway. The isoclines (lines of different colors) represent iso-lines with 95% bootstrap confidence limits. The effect of geographic location was estimated as smooth functions of longitude and latitude (thin-plate regression spline with maximally 11° of freedom) by using GAM also accounting for effects of species and temporal trends (Fig. 1B).
Fig. 3.
Fig. 3.
Climatic effects on interannual changes in fruiting of 83 fungal species. Temperature and precipitation variables are referring to either the preceding year (t − 1) or the same year (t) as fungal fruiting. The climatic effects shown were estimated as linear or smooth terms in one GAM also accounting for location and species effects (SI Table 2). Whole and broken lines indicate fitted partial effects with 95% bootstrap confidence limits. The tick marks on the x axis show the location of the covariates (see also SI Fig. 4, showing partial residuals).

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