Elsevier

Fungal Ecology

Volume 23, October 2016, Pages 30-41
Fungal Ecology

Meteorological conditions and site characteristics driving edible mushroom production in Pinus pinaster forests of Central Spain

https://doi.org/10.1016/j.funeco.2016.05.008Get rights and content

Abstract

Integrating fungal-based ecosystem services into forest management planning and policy-making requires quantitative knowledge of the yields of fungal sporocarps and their environmental drivers. The aim of this study was to predict edible mushroom yield in Pinus pinaster forests of Central Spain, based on a 17-year data series. Two-stage mixed-effects models were used to examine the effect of predictors on mushroom occurrence and yield separately with the aim of providing further insight into the ecological system. Changes in seasonal precipitation represented the main weather-related driver affecting sporocarp emergence and production, since they were both positively influenced by late summer and early autumn precipitation. Soil acidity positively influenced Lactarius yield. Stand age and sandy soils showed a negative influence on mushroom production. The diversity of drivers became more apparent at the fungal species level. The models can be used for predicting the production of edible fungi under different meteorological and site conditions.

Introduction

Wild edible fungi are among the most important non-wood forest products (NWFPs) due to their commercial and recreational importance as a food source (Boa, 2004). Therefore, they represent a key element of provisioning and cultural fungal-based ecosystem services such as wild food, leisure, tourism and marketed goods (Martínez de Aragón et al., 2011, Schulp et al., 2014). Indeed, the market demand for many ectomycorrhizal fungi has increased to the extent that the value of forest fungi may equal or even surpass the value of timber (Alexander et al., 2002, Palahí et al., 2009). Central Spain, where mushroom harvesting has become a major activity in Pinus pinaster forests (Fernández-Toirán et al., 2006), is not an exception, and the revenue from mushroom collection is approaching the return expected from timber, which has been the most important forest product during the last decade (Ágreda et al., 2013). Some of the fungi found in P. pinaster forests, such as Lactarius group deliciosus, are highly appreciated locally and internationally, and their trade has become an important complementary economic activity in many regions (Voces et al., 2011, Cai et al., 2011, Martínez de Aragón et al., 2011).

The increasing socioeconomic importance of wild edible mushrooms coupled with other factors like the decrease in the profitability of wood production is making forest and land managers increasingly consider inventorying and predicting fungal yields, to integrate edible mushroom production into forest management planning (Pilz and Molina, 2002, Mogas et al., 2006, Aldea et al., 2014). The integration of mushroom production into forest management planning requires quantitative knowledge, and prediction, of edible mushroom yields and its environmental drivers. Several factors affecting mushroom yield and dynamics have been indicated in the literature. These factors are classified into three main groups, which are: stand structure (e.g. tree species, stand density, stand age), weather variability (e.g. precipitation, temperature) and local site characteristics (e.g. altitude, slope, aspect) (Martínez-Peña et al., 2012a). The large number of potential variables related to mushroom productivity, and their interdependence, makes it difficult to estimate mushroom yields. According to previous research, beyond stand structure or site characteristics, the variables that affect mushroom yield the most are related to meteorological conditions (Martínez-Peña et al., 2012b, Bonet et al., 2012, Hernández-Rodríguez et al., 2015).

Modeling techniques are valuable tools that allow identifying factors most relevant for predicting mushroom yield. Empirical models based on long historical data series of annual measurements in many locations can be used to model mushroom yields as a function of different types of predictors. In general, there are very few models in the literature aiming at predicting the yield of non-wood forest products to be used in forest planning (Bravo et al., 2011). Although these kinds of studies are rather recent, several mushroom yield models have been published so far (Bonet et al., 2008, Bonet et al., 2010, Bonet et al., 2012, Martínez-Peña et al., 2012b, de-Miguel et al., 2014, Ágreda et al., 2015, Hernández-Rodríguez et al., 2015). Mushroom yield modeling requires large quantities of data over several years in order to provide reliable estimates, especially if the models are intended to account for the effect of meteorological conditions. The difficulty in obtaining such long historical datasets for modeling the effect of weather variables is the reason behind the rather limited number of such mushroom yield models.

The aim of this study was to develop models for estimating the occurrence and production (i.e., fresh weight) of edible mushrooms in P. pinaster forests of Central Spain in relation to the provision of fungal-based provisioning ecosystem services, by accounting for the effect of stand, site and meteorological conditions based on data gathered during seventeen consecutive years (1997-2013).

Section snippets

Study area

The study area was located in the so-called ‘Pinares Llanos de Almazán’ area, Soria province, Castilla y León region, Central Spain (Fig. 1). Altitude ranges from 1000 to 1200 m.a.s.l. and soils are Arenosols and Regosols developed over tertiary and quaternary sands. The annual mean temperature is 10.6 °C, the daily mean maximum temperature is 16.7 °C, and the annual absolute maximum temperature is 38 °C. The daily mean minimum temperature is 4.5 °C, and the annual mean minimum temperature is

Models for the probability of mushroom occurrence

The models selected for predicting the probability of occurrence of edible, marketed and L. group deliciosus mushrooms according to the model selection and evaluation criteria are presented in Table 3 (i.e., denoted as Eq. (1)) along with the information about the uncertainty of the estimates. Similarly, the corresponding standard deviation of the year random effects are presented in Table 4 along with their bootstrapped confidence intervals.

The logistic regression analyses showed that the

Discussion

Our results show the strong influence of the meteorological conditions on the appearance of fungal fruit bodies and mushroom yield. It was seen that stand and soil characteristics become significant predictors as we narrow down from a broad category like edible fungi to the species level of L. group deliciosus. This revealed the distinct autecology and requirements of different fungal genera and species for sporocarp fructification and mushroom productivity. The higher between-year random

Acknowledgments

This study was partially funded by the research projects AGL2012-40035-C03-01 and AGL2012-40035-C03-03 (Ministerio de Economía y Competitividad of Spain, Secretaría de Estado de Investigación, Desarrollo e Innovación), by the Micosylva + project (Interreg IVB SUDOE SOE3/P2/E533), and by the Mycological Programme of Castilla y Leon (www.micocyl.es). This study also received funding from the European Union's Horizon 2020 research and innovation programme within the framework of the

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