Predictive empirical models for mushroom production in ladanifer stands. Guzman y Vargas (Molecular Phylogenetics and Evolution Volume 37, Issue 3 644-6 Fig. Distribution map and number of species. Pie diagrams include proportion of whiteflowered (white) and purple-flowered (grey) species in every country. Fig. Distribution map and number of species. Pie diagrams include proportion of whiteflowered (white) and purple-flowered (grey) species in every country. María Hernández-Rodríguez Sustainable Forest Management Research Institute University of Valladolid Widely distributed in Mediterranean area Poor and stony soils Spain: 2, mill. ha COST Action FP13 European Non-Wood Forest Products (NWFPs) Network Pyrophytic ecology Flammability (mature stands) Dry stems covered by lichens Flammable papery bark High forest fire risk Difficult extinction Worthless unproductive ecosystems? Protective value Wildlife shelter Beekeeping flora Medicinal value Use in perfume industry 1
Objective Worthless unproductive ecosystems? High mushroom production High fungal diversity Early production of edible species Calcicolous Tuber melanosporum Tuber aestivum To develop predictive empirical models for mushroom production in ladanifer shrublands in order to provide a useful tool for the optimal management of these areas. Siliceous Boletus edulis Boletus aereus Cantharellus cibarius Amanita caesarea Mycorrhizal reservoir Fire prevention Management Economic benefit from NWFP Permanent plots 2
Total clearing Fire/Controlled burning Years after clearing 1 2 3 4 Sampling Year 12 6 7 8 9 12 Years after fire 1 Sampling Year 12 2 3 4 6 7 8 12 9 12 14 1 3 4 6 3 16 4 17 18 19 21 22 23 24 2 12 6 Sampling Laboratory work 3
Data analysis Data analysis Mushroom production and diversity models Mycorrhizal and saprotrophic taxa: Mushroom production and diversity models Production (kg ha-1) Diversity: Shannon Index Nonlinear regression analysis and fixed-effects modeling approach The effect of treatment was tested using a dummy variable Evaluation criteria: H = - pi (ln pi) pi: relative importance of each sp. Boletus edulis production (kg ha-1) Predictors: Climatic variablestreatment Time after treatment Vegetation structure Accordance with current scientific knowledge Logical behaviour of the models in extrapolations Simplicity Statistical significance (p-value <.). Vegetation structure models Prediction of missing values Test of different growth functions Results: Vegetation models Mean height Results: Vegetation models Canopy Cover VAN DER VLIET Canopy cover (%) 1 8 GOMPERTZ Fire Total clearing 1 2 3 HMED exp.73-3.3349 exp -.34492Y Residual standard error: 18. 3 1 2 3 3 2Y ( 2.7982 1.76 TREAT ) 2Y 2Y 2 e CC 79.767 1 1 2 2.7982 1.76 TREAT 2.7982 1.76 TREAT Residual standard error: 12.39 4
Results: Production Results : Production 1 1 1 Residual standard error: 7.7 Myco exp( 4.788 2.4323 ln(tm min O ) 4.31 Y.7497Y ) 3 1 2 2 3 2 1 1 Residual standard error:.73 Results: Diversity 1 2 1 Myco exp( 2. 3987. 4837 T min S O. 476 PS. 18691 Y 1. 38384 Y ) Residual standard error:.66 Residual standard error:.4641 1 2 8 Canopy cover (%) Sapro exp(.1733.37 T min O N D.9Y.4442 Y Residual standard error:.4383 Myco exp( 6.9376.76 Tm min S O.49 PA S.43 H.922719 H ) 2... 1. 2. 1. 1. 2.. Saprotrophic Shannon Diversity Index 3.. 1. 1. 2. 2. 2. Saprotrophic diversity Average conditions Wet and warm conditions Dry and cold conditions Wet and cold conditions Dry and warm conditions... Average conditions Wet and warm conditions Dry and cold conditions Wet and cold conditions Dry and warm conditions Mycorrhizal Shannon Diversity Index 1. 1. 2. 2. Mycorrhizal diversity Mycorrhizal Shannon Diversity Index 1 TOTAL CLEARING Sapro exp( 4.99 3.942 ln(tm min O N ).8398 Y ) Results: Diversity Residual standard error: 7.33 Residual standard error:.6 Sapro exp( 34.716 12.34 ln(tm min S O N D ).814 H ) Myco exp( 9.4429 1.738 Tm min O 2.4366 H.11 H ) 1 2 1. FIRE. Saprotrophic Shannon Diversity Index 3 Mycorrhizal production (kg ha-1) 3 Mycorrhizal production (kg ha-1) Saprotrophic production Mycorrhizal production Sapro exp(.2681.4196 T min O N.6 CC.1993 ln(cc.1)) Residual standard error:.3988
Results: Boletus edulis production Results: Boletus edulis production 3 Boletus edulis production (kg ha-1) CC=8% CC=76% CC=72% CC=84% CC=88% 3 Boletus edulis production (kg ha-1) 3 H=1cm H=cm H=1cm H=16cm H=18cm 1 2 B.edulis exp( 17.94.2161 Ts o 8.798 log( Y.1 ).6478 Y ) Residual standard error: 14.22 Conclusions These models can be a useful tool for the optimal management of these areas in order to enhance fungal production while preventing forest fires. Models for mushroom production and diversity can be applied from both, inventory data or management history data of the scrublands. Although precipitation was not present in most of the models, this does not mean that it has no influence in mushroom fructification because it is correlated with temperatures. No significant differences were found for the two studied treatments. Mycorrhizal taxa are influenced by earlier temperature (September and October) whereas saprotrophic taxa depend on later temperatures (October, November and December). Boletus edulis is the most economically valuable species in this ecosystems and can be found from -6 years after treatment to the end of ladanifer life cycle (multistage species). Boletus edulis production (kg ha-1) Boletus edulis production 7 Boletus edulis production 8 Canopy cover (%) 1 B.edulis exp( 137.3669 Tm min S O.8 H.891 H.4 CC 87. ln( CC.1 )) Residual standard error: 12.48 Acknowledges FPI-Uva Grant 6
Acknowledges Thank you for your attention Antonio Rodríguez Sergio de Miguel Timo Pukkala Juan Andrés Oria de Rueda Pablo Martín-Pinto Raúl Fraile Domingo Ferrero 7