The Experts below are selected from a list of 3588 Experts worldwide ranked by ideXlab platform
Rafael Calama - One of the best experts on this subject based on the ideXlab platform.
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Understanding Tree-to-Tree Variations in Stone Pine (Pinus Pinea L.) Cone Production Using Terrestrial Laser Scanner
Remote Sensing, 2020Co-Authors: Robert Schneider, Rafael Calama, Olivier Martin-ducupAbstract:Kernels found in Stone Pinecones are of great economic value, often surpassing timber income for most forest owners. Visually evaluating cone production on standing trees is challenging since the cones are located in the sun-exposed part of the crown, and covered by two vegetative shoots. Very few studies were carried out in evaluating how new remote sensing technologies such as terrestrial laser scanners (TLS) can be used in assessing cone production, or in trying to explain the tree-to-tree variability within a given stand. Using data from 129 trees in 26 plots located in the Spanish Northern Plateau, the gain observed by using TLS data when compared to traditional inventory data in predicting the presence, the number, and the average weight of the cones in an individual tree was evaluated. The models using TLS-derived metrics consistently showed better fit statistics, when compared to models using traditional inventory data pertaining to site and tree levels. Crown dimensions such as projected crown area and crown volume, crown density, and crown asymmetry were the key TLS-derived drivers in understanding the variability in inter-tree cone production. These results underline the importance of crown characteristics in assessing cone production in Stone Pine. Moreover, as cone production (number of cones and average weight) is higher in crowns with lower density, the use of crown pruning, abandoned over 30 years ago, might be the key to increasing production in combination with stand density management
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Thinning increases cone production of Stone Pine (Pinus Pinea L.) stands in the Northern Plateau (Spain)
Annals of Forest Science, 2013Co-Authors: Daniel Moreno-fernández, Rafael Calama, Javier Gordo, Isabel Canellas, Mariola Sánchez-gonzálezAbstract:Context Edible Stone Pine ( Pinus Pinea L.) nut is a forest product which provides the highest incomes to the owners of Stone Pine forests. Aim The objective of this work is to evaluate the effect of first thinning on growth and cone production in an artificially regenerated stand in order to determine optimum intensity. Methods A thinning trial was installed in 2004 to compare two thinning regimes (heavy and moderate) and a control treatment. From 2004 to 2012, six inventories of forest attributes were carried out, and the cone crop was harvested annually. We evaluated the effect of thinnings on growth using repeated measures analysis of variance with a mixed model approach. With regards to cone production, we first estimated the probability of finding cones in a tree by applying a generalized mixed model and then estimated cone production by using a mixed model, including climatic variables. Results We found that thinning had a positive influence on tree diameter increment. Thinning increased the probability of finding cones and cone production. However, significant differences between heavy and moderate thinnings were not found. Conclusion We recommend early silvicultural treatments in Stone Pine stands to favor the development of trees and larger edible Pine nut production.
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modelling spatial and temporal variability in a zero inflated variable the case of Stone Pine pinus Pinea l cone production
Ecological Modelling, 2011Co-Authors: Rafael Calama, Javier Gordo, Sven Mutke, Gregorio Montero, Jose Tome, Margarida TomeAbstract:Abstract Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone Pine (Pinus Pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of Stone Pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 Stone Pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in Stone Pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.
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landowner net benefit from Stone Pine pinus Pinea l afforestation of dry land cereal fields in valladolid spain
Journal of Forest Economics, 2010Co-Authors: Paola Ovando, Rafael Calama, Pablo Campos, Gregorio MonteroAbstract:Abstract This analysis measures the net benefit that a landowner could obtain from changing current dry-land cereal fields into Stone Pine plantations in Portillo and Viana (Valladolid, Spain). We apply cost–benefit analysis techniques to estimate the present value of Stone Pine afforestation net benefit by considering an infinite series of forestry rotations. We simulate three Stone Pine silviculture models at each of the two sites. In addition, we estimate landowner extended net benefits from Stone Pine afforestation when we consider a hypothetical payment for the carbon sequestration service. Results show that, when government subsidies are included, Stone Pine afforestation only offers positive landowner net benefit in Portillo when both medium and high-stocking silviculture models are applied. Taking into account carbon prices up to €45 tC −1 (€12.3 tCO 2 −1 ), Stone Pine afforestation gives landowner positive extended net benefits for the three silviculture models simulated at the Portillo and Viana sites.
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effect of stand structure on Stone Pine pinus Pinea l regeneration dynamics
Forestry, 2008Co-Authors: Ignacio Barbeito, Rafael Calama, Marta Pardos, Isabel CanellasAbstract:Summary Natural regeneration of Stone Pine ( Pinus Pinea L.) in the Northern Plateau of Spain is fraught with problems and, consequently, diffi cult to attain. In this study, we start by describing the spatial structure of one even-aged and one uneven multi-aged stand as a fi rst step towards understanding the processes that produce the spatial patterns and, in turn, provide managers with information that could help to enhance regeneration. All trees were mapped and located through their xy coordinates and two perpendicular crown diameter measurements were recorded for each tree in addition to other structural variables. A grid-based approach, in which crowns were projected on a grid, was then used to characterize the spatial pattern and this was compared with the conventional point pattern analysis. This allowed us to take into account variations in crown size and shape. Regeneration was found to be clumped in both stands and the spatial association with stems varied among the age classes considered. Results from the crown pattern analysis differed from those obtained using the traditional point pattern analysis, especially in the older age classes, where crowns were larger and had a greater infl uence on regeneration. Our results suggest that where large variations in crown dimensions exist, the use of this method can help us to avoid misinterpretations of the results and provide further insight into the processes that drive natural regeneration.
Gregorio Montero - One of the best experts on this subject based on the ideXlab platform.
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Decline in commercial Pine nut and kernel yield in Mediterranean Stone Pine (Pinus Pinea L.) in Spain
Iforest - Biogeosciences and Forestry, 2020Co-Authors: R. Calama, Javier Gordo, Sven Mutke, M. Conde, G. Madrigal, E. Garriga, M.j. Arias, Míriam Piqué, R. Gandía, Gregorio MonteroAbstract:Abstract: Cones of the Mediterranean Stone Pine (Pinus Pinea L.) constitute one of the most relevant non-wood forest products collected in the Mediterranean forests, providing high value edible kernels. In the last years it has been observed a severe decline in the kernel-per-cone yield (kg of kernels obtained from a kg of fresh cones) through the whole area of the species. This decline has been associated with both ongoing climate change and the recent expansion over the Mediterranean Basin of the Western Conifer Seed Bug, Leptoglossus occidentalis Heideman, an exotic pest which predates seeds of conifer species. In the present work we aimed to confirm and quantify the impact of this recent decline on Pine nut and kernel production, identify the main factors provoking this reduction, and give evidence over causality by a potential biotic agent. We analysed recent and historical series of Pine nut and kernel production obtained in the four main regions where Pinus Pinea occurs in Spain. Our results showed a significant drop in the final kernel-per-cone yield on three of the four regions analysed, reaching reductions over 50% in the most affected areas. We observed that this reduction is mainly associated with a significant and generalised drop in the kernel-per-nut yield (kg of kernels per kg of Pine nuts in shell), triggered by an increment in the rate of damaged Pine nuts and, to a lesser extent, a reduction in the number of Pine nuts per cone. The prevalence of this reduction on kernel-per-cone yield over different years and provenances with contrasting climate reinforces the hypothesis of the implication of a biotic factor which can be aggravated on extreme drought years.
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generalized biomass equations for Stone Pine pinus Pinea l across the mediterranean basin
Forest Ecology and Management, 2018Co-Authors: Alexandra Correia, Gregorio Montero, Andrea Cutini, Francesco Chianucci, Maria Chiara Manetti, Sonia Pacheco Faias, Ricardo Ruizpeinado, Luis Fernando Oliveira Fontes, Paula Soares, Margarida TomeAbstract:Abstract Accurate estimates of tree biomass are strongly required for forest carbon budget estimates and to understand ecosystem dynamics for a sustainable management. Existing biomass equations for Mediterranean species are scarce, stand- and site-specific and therefore are not suitable for large scale application. In this study, biomass allometric equations were developed for Stone Pine (Pinus Pinea L.), a Mediterranean tree species with relevant ecologic and economic interest. A dataset of 283 harvested trees was compiled with above- and belowground biomass from 16 sites in three countries (Italy, Spain, Portugal) representative of the species’ geographical Mediterranean distribution. A preliminary approach comparing the ordinary least squares method and the mixed model approach was performed in order to evaluate the most appropriate method for nested data in the absence of calibration data. To quantify the sources of error associated with applying biomass equations beyond the geographical range of the data used to develop them, a residual analysis was conducted. The allometric analysis showed low intra-specific variability in aboveground biomass relationships, which was relatively insensitive to the stand and site conditions. Significant differences were found for the crown components (needles and branches), which may be attributed to local geographical adaptation, site conditions and stand management. The root biomass was highly correlated with diameter at breast height irrespective of the geographical origin. Biased estimates were found when using site-specific equations outside the geographical range from where they were developed. The new biomass equations improved the accuracy of biomass estimates, particularly for the aboveground components of higher dimension trees and for the root component, being highly suitable for use in regional and national biomass forest calculations. It is, up to the present, the most complete database of harvested Stone Pine trees worldwide.
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modelling spatial and temporal variability in a zero inflated variable the case of Stone Pine pinus Pinea l cone production
Ecological Modelling, 2011Co-Authors: Rafael Calama, Javier Gordo, Sven Mutke, Gregorio Montero, Jose Tome, Margarida TomeAbstract:Abstract Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone Pine (Pinus Pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of Stone Pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 Stone Pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in Stone Pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.
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landowner net benefit from Stone Pine pinus Pinea l afforestation of dry land cereal fields in valladolid spain
Journal of Forest Economics, 2010Co-Authors: Paola Ovando, Rafael Calama, Pablo Campos, Gregorio MonteroAbstract:Abstract This analysis measures the net benefit that a landowner could obtain from changing current dry-land cereal fields into Stone Pine plantations in Portillo and Viana (Valladolid, Spain). We apply cost–benefit analysis techniques to estimate the present value of Stone Pine afforestation net benefit by considering an infinite series of forestry rotations. We simulate three Stone Pine silviculture models at each of the two sites. In addition, we estimate landowner extended net benefits from Stone Pine afforestation when we consider a hypothetical payment for the carbon sequestration service. Results show that, when government subsidies are included, Stone Pine afforestation only offers positive landowner net benefit in Portillo when both medium and high-stocking silviculture models are applied. Taking into account carbon prices up to €45 tC −1 (€12.3 tCO 2 −1 ), Stone Pine afforestation gives landowner positive extended net benefits for the three silviculture models simulated at the Portillo and Viana sites.
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an empirical ecological type model for predicting Stone Pine pinus Pinea l cone production in the northern plateau spain
Forest Ecology and Management, 2008Co-Authors: Rafael Calama, Sven Mutke, Fco Javier Gordo, Gregorio MonteroAbstract:Abstract Data from a 10 year series of cone production taken from 755 trees were used to model individual cone production in Stone Pine (Pinus Pinea L.) stands in the Northern Inland Plateau of Spain following three different approaches. The first step was the construction of a silvicultural model, including typical forest growth covariates as tree size, stand density, site index and distance independent competition indices. Remaining between-plot variability was related with ecological attributes, as winter rainfall and altitude, resulting in a hybrid model. The third approach attempted to develop an ecological-type based model by considering a previous stratification of Stone Pine forests based on altitude, soil, geology and climate characteristics. The best model in terms of likelihood, bias and accuracy on predictions was the ecological-type one, producing unbiased marginal estimates for the main part of the territory with an efficiency reaching up to 39%. Due to the hierarchical structure of data set, proposed model was formulated as a multilevel mixed model. Stochastic formulation allows simulating cone production under different changing scenarios and describing real distribution of cone production within a given stand. Developed model constitutes the cone yield module for PineA2, an integrated single tree model for the management of Stone Pine stands within the northern Plateau of Spain.
Sven Mutke - One of the best experts on this subject based on the ideXlab platform.
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weather as main driver for masting and stem growth variation in Stone Pine supports compatible timber and nut co production
Agricultural and Forest Meteorology, 2021Co-Authors: Tatiana A Shestakova, Javier Gordo, Sven Mutke, Julio J Camarero, Ester Sin, Jesus Peman, Jordi VoltasAbstract:Abstract Trade-offs between life-history traits are common in plants, and those involving growth and reproduction may be evident during mast years. The nutlike seeds of the Stone Pine (Pinus Pinea L.) stand out among the most appreciated Mediterranean forest products, but its lengthy reproductive cycle makes the identification of masting mechanisms challenging. In the Spanish Northern Plateau, Stone Pine woodlands are managed as multifunctional forests. Here, we investigated whether timber and nut production are compatible goals in the region. Temporal ring-width and cone yield patterns were characterised in five monospecific stands since 1960. At tree level, we found an equivalent allocation of resources to reproductive and non-reproductive (aboveground) biomass for an average year, but harvest index exceeded 80% during mast years. These large yields, however, did not impose a penalty on aboveground biomass increment. Regionally, we reported a slightly larger magnitude of high-frequency synchronous growth (â = 0.50) compared with that of reproduction (â = 0.42), which is important to contextualise the ecological and economical relevance of masting for the species. By investigating growth-yield interannual dynamics, we found that both traits were strongly and positively correlated, although with a 3-year lag. Therefore, years favouring a high growth coincided with large conelet emergences leading to abundant seed rains to occur three years later, which pointed to key environmental drivers common to both traits. Actually, radial growth and reproduction partly responded to the same climate factors, with climate three years before seed rain being related to masting in a similar way as it was related to ring-width of this same year. Our results provide evidence for the proposed link between masting and growth, and suggest that resources are not diverted from growth during cone filling in Stone Pine. We conclude that timber production and nut production are perfectly compatible in this species.
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Decline in commercial Pine nut and kernel yield in Mediterranean Stone Pine (Pinus Pinea L.) in Spain
Iforest - Biogeosciences and Forestry, 2020Co-Authors: R. Calama, Javier Gordo, Sven Mutke, M. Conde, G. Madrigal, E. Garriga, M.j. Arias, Míriam Piqué, R. Gandía, Gregorio MonteroAbstract:Abstract: Cones of the Mediterranean Stone Pine (Pinus Pinea L.) constitute one of the most relevant non-wood forest products collected in the Mediterranean forests, providing high value edible kernels. In the last years it has been observed a severe decline in the kernel-per-cone yield (kg of kernels obtained from a kg of fresh cones) through the whole area of the species. This decline has been associated with both ongoing climate change and the recent expansion over the Mediterranean Basin of the Western Conifer Seed Bug, Leptoglossus occidentalis Heideman, an exotic pest which predates seeds of conifer species. In the present work we aimed to confirm and quantify the impact of this recent decline on Pine nut and kernel production, identify the main factors provoking this reduction, and give evidence over causality by a potential biotic agent. We analysed recent and historical series of Pine nut and kernel production obtained in the four main regions where Pinus Pinea occurs in Spain. Our results showed a significant drop in the final kernel-per-cone yield on three of the four regions analysed, reaching reductions over 50% in the most affected areas. We observed that this reduction is mainly associated with a significant and generalised drop in the kernel-per-nut yield (kg of kernels per kg of Pine nuts in shell), triggered by an increment in the rate of damaged Pine nuts and, to a lesser extent, a reduction in the number of Pine nuts per cone. The prevalence of this reduction on kernel-per-cone yield over different years and provenances with contrasting climate reinforces the hypothesis of the implication of a biotic factor which can be aggravated on extreme drought years.
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Molecular and quantitative genetics of Stone Pine (Pinus Pinea)
2019Co-Authors: Sven Mutke, Bruno Fady, Giovanni Vendramin, Francesca Bagnoli, Santiago González-martínezAbstract:The Mediterranean Stone Pine is currently on its way to domestication. Its genuine Mediterranean Pine nuts are among the most expensive nuts in the world because they are mainly wild-collected from Pine forests and woodlands. Despite the wide current distribution of Stone Pine over the whole Mediterranean biome, old-growth forests are scarce, often associated locally with dynamics on lose sands, coastal dunes or former estuary marshes. The species has been found to be genetically depauperate, putatively due to a population bottleneck in a local refugium during the Last Glacial Maximum confirmed in southern Iberia, and a possibly anthropic range expansion during Holocene. Only recently, cone harvesting and processing mechanisation have allowed for profitable Pine nut production from orchard plantations. In Spain and Portugal, first elite clones have been registered for their use as grafted orchard crop.
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modelling spatial and temporal variability in a zero inflated variable the case of Stone Pine pinus Pinea l cone production
Ecological Modelling, 2011Co-Authors: Rafael Calama, Javier Gordo, Sven Mutke, Gregorio Montero, Jose Tome, Margarida TomeAbstract:Abstract Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone Pine (Pinus Pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of Stone Pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 Stone Pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in Stone Pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.
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phenotypic plasticity is stronger than adaptative differentiation among mediterranean Stone Pine provenances
Forest Systems, 2010Co-Authors: Sven Mutke, Javier Gordo, Regina M Chambel, Aranzazu M Prada, Daniel Alvarez, S Iglesias, Luis GilAbstract:The Mediterranean Stone Pine, Pinus Pinea L., seems to be well adapted to the different climate zones of its distribution range that spans four thousand kilometres along the Northern shore of the Mediterranean Sea. But recent molecular studies revealed it to be extremely genetically depauperate for a widespread tree. In this context, a provenances trial should elucidate whether any differentiation in adaptative traits can be identified between 34 accessions covering its natural range. The presence of strong spatial autocorrelations throughout four test sites required iterative nearest-neighbours adjustments in their statistical analysis. No significant differences in survival or ontogeny were found between accessions, while height growth was slightly though significantly more vigorous in northern or inland provenances. But these differences were masked by a common, stable reaction norm in dependence on site and microsite. On the other hand, its strong developmental plasticity allows the Stone Pine to delay the heteroblastic phase change in order to survive in unfavourable conditions, a clear advantage in the limiting and unpredictable environments of Mediterranean ecosystems.
Javier Gordo - One of the best experts on this subject based on the ideXlab platform.
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weather as main driver for masting and stem growth variation in Stone Pine supports compatible timber and nut co production
Agricultural and Forest Meteorology, 2021Co-Authors: Tatiana A Shestakova, Javier Gordo, Sven Mutke, Julio J Camarero, Ester Sin, Jesus Peman, Jordi VoltasAbstract:Abstract Trade-offs between life-history traits are common in plants, and those involving growth and reproduction may be evident during mast years. The nutlike seeds of the Stone Pine (Pinus Pinea L.) stand out among the most appreciated Mediterranean forest products, but its lengthy reproductive cycle makes the identification of masting mechanisms challenging. In the Spanish Northern Plateau, Stone Pine woodlands are managed as multifunctional forests. Here, we investigated whether timber and nut production are compatible goals in the region. Temporal ring-width and cone yield patterns were characterised in five monospecific stands since 1960. At tree level, we found an equivalent allocation of resources to reproductive and non-reproductive (aboveground) biomass for an average year, but harvest index exceeded 80% during mast years. These large yields, however, did not impose a penalty on aboveground biomass increment. Regionally, we reported a slightly larger magnitude of high-frequency synchronous growth (â = 0.50) compared with that of reproduction (â = 0.42), which is important to contextualise the ecological and economical relevance of masting for the species. By investigating growth-yield interannual dynamics, we found that both traits were strongly and positively correlated, although with a 3-year lag. Therefore, years favouring a high growth coincided with large conelet emergences leading to abundant seed rains to occur three years later, which pointed to key environmental drivers common to both traits. Actually, radial growth and reproduction partly responded to the same climate factors, with climate three years before seed rain being related to masting in a similar way as it was related to ring-width of this same year. Our results provide evidence for the proposed link between masting and growth, and suggest that resources are not diverted from growth during cone filling in Stone Pine. We conclude that timber production and nut production are perfectly compatible in this species.
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Decline in commercial Pine nut and kernel yield in Mediterranean Stone Pine (Pinus Pinea L.) in Spain
Iforest - Biogeosciences and Forestry, 2020Co-Authors: R. Calama, Javier Gordo, Sven Mutke, M. Conde, G. Madrigal, E. Garriga, M.j. Arias, Míriam Piqué, R. Gandía, Gregorio MonteroAbstract:Abstract: Cones of the Mediterranean Stone Pine (Pinus Pinea L.) constitute one of the most relevant non-wood forest products collected in the Mediterranean forests, providing high value edible kernels. In the last years it has been observed a severe decline in the kernel-per-cone yield (kg of kernels obtained from a kg of fresh cones) through the whole area of the species. This decline has been associated with both ongoing climate change and the recent expansion over the Mediterranean Basin of the Western Conifer Seed Bug, Leptoglossus occidentalis Heideman, an exotic pest which predates seeds of conifer species. In the present work we aimed to confirm and quantify the impact of this recent decline on Pine nut and kernel production, identify the main factors provoking this reduction, and give evidence over causality by a potential biotic agent. We analysed recent and historical series of Pine nut and kernel production obtained in the four main regions where Pinus Pinea occurs in Spain. Our results showed a significant drop in the final kernel-per-cone yield on three of the four regions analysed, reaching reductions over 50% in the most affected areas. We observed that this reduction is mainly associated with a significant and generalised drop in the kernel-per-nut yield (kg of kernels per kg of Pine nuts in shell), triggered by an increment in the rate of damaged Pine nuts and, to a lesser extent, a reduction in the number of Pine nuts per cone. The prevalence of this reduction on kernel-per-cone yield over different years and provenances with contrasting climate reinforces the hypothesis of the implication of a biotic factor which can be aggravated on extreme drought years.
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Thinning increases cone production of Stone Pine (Pinus Pinea L.) stands in the Northern Plateau (Spain)
Annals of Forest Science, 2013Co-Authors: Daniel Moreno-fernández, Rafael Calama, Javier Gordo, Isabel Canellas, Mariola Sánchez-gonzálezAbstract:Context Edible Stone Pine ( Pinus Pinea L.) nut is a forest product which provides the highest incomes to the owners of Stone Pine forests. Aim The objective of this work is to evaluate the effect of first thinning on growth and cone production in an artificially regenerated stand in order to determine optimum intensity. Methods A thinning trial was installed in 2004 to compare two thinning regimes (heavy and moderate) and a control treatment. From 2004 to 2012, six inventories of forest attributes were carried out, and the cone crop was harvested annually. We evaluated the effect of thinnings on growth using repeated measures analysis of variance with a mixed model approach. With regards to cone production, we first estimated the probability of finding cones in a tree by applying a generalized mixed model and then estimated cone production by using a mixed model, including climatic variables. Results We found that thinning had a positive influence on tree diameter increment. Thinning increased the probability of finding cones and cone production. However, significant differences between heavy and moderate thinnings were not found. Conclusion We recommend early silvicultural treatments in Stone Pine stands to favor the development of trees and larger edible Pine nut production.
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modelling spatial and temporal variability in a zero inflated variable the case of Stone Pine pinus Pinea l cone production
Ecological Modelling, 2011Co-Authors: Rafael Calama, Javier Gordo, Sven Mutke, Gregorio Montero, Jose Tome, Margarida TomeAbstract:Abstract Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone Pine (Pinus Pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of Stone Pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 Stone Pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in Stone Pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.
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phenotypic plasticity is stronger than adaptative differentiation among mediterranean Stone Pine provenances
Forest Systems, 2010Co-Authors: Sven Mutke, Javier Gordo, Regina M Chambel, Aranzazu M Prada, Daniel Alvarez, S Iglesias, Luis GilAbstract:The Mediterranean Stone Pine, Pinus Pinea L., seems to be well adapted to the different climate zones of its distribution range that spans four thousand kilometres along the Northern shore of the Mediterranean Sea. But recent molecular studies revealed it to be extremely genetically depauperate for a widespread tree. In this context, a provenances trial should elucidate whether any differentiation in adaptative traits can be identified between 34 accessions covering its natural range. The presence of strong spatial autocorrelations throughout four test sites required iterative nearest-neighbours adjustments in their statistical analysis. No significant differences in survival or ontogeny were found between accessions, while height growth was slightly though significantly more vigorous in northern or inland provenances. But these differences were masked by a common, stable reaction norm in dependence on site and microsite. On the other hand, its strong developmental plasticity allows the Stone Pine to delay the heteroblastic phase change in order to survive in unfavourable conditions, a clear advantage in the limiting and unpredictable environments of Mediterranean ecosystems.
Margarida Tome - One of the best experts on this subject based on the ideXlab platform.
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generalized biomass equations for Stone Pine pinus Pinea l across the mediterranean basin
Forest Ecology and Management, 2018Co-Authors: Alexandra Correia, Gregorio Montero, Andrea Cutini, Francesco Chianucci, Maria Chiara Manetti, Sonia Pacheco Faias, Ricardo Ruizpeinado, Luis Fernando Oliveira Fontes, Paula Soares, Margarida TomeAbstract:Abstract Accurate estimates of tree biomass are strongly required for forest carbon budget estimates and to understand ecosystem dynamics for a sustainable management. Existing biomass equations for Mediterranean species are scarce, stand- and site-specific and therefore are not suitable for large scale application. In this study, biomass allometric equations were developed for Stone Pine (Pinus Pinea L.), a Mediterranean tree species with relevant ecologic and economic interest. A dataset of 283 harvested trees was compiled with above- and belowground biomass from 16 sites in three countries (Italy, Spain, Portugal) representative of the species’ geographical Mediterranean distribution. A preliminary approach comparing the ordinary least squares method and the mixed model approach was performed in order to evaluate the most appropriate method for nested data in the absence of calibration data. To quantify the sources of error associated with applying biomass equations beyond the geographical range of the data used to develop them, a residual analysis was conducted. The allometric analysis showed low intra-specific variability in aboveground biomass relationships, which was relatively insensitive to the stand and site conditions. Significant differences were found for the crown components (needles and branches), which may be attributed to local geographical adaptation, site conditions and stand management. The root biomass was highly correlated with diameter at breast height irrespective of the geographical origin. Biased estimates were found when using site-specific equations outside the geographical range from where they were developed. The new biomass equations improved the accuracy of biomass estimates, particularly for the aboveground components of higher dimension trees and for the root component, being highly suitable for use in regional and national biomass forest calculations. It is, up to the present, the most complete database of harvested Stone Pine trees worldwide.
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linear mixed modelling of cone production for Stone Pine in portugal
Silva Lusitana, 2014Co-Authors: Abel Rodrigues, Giovani L Silva, Miguel Casquilho, Joao P B Freire, Isabel Carrasquinho, Margarida TomeAbstract:This study aimed to model the cone production weight of Stone Pine ( Pinus Pinea L.) trees using two approaches: classic linear mixed modelling and Bayesian mixed modelling. The field data were collected in the Setubal Peninsula, the main production area in Portugal, where 51 plots for monitoring cone production per tree during three production periods (2004-2005, 2005-2006 and 2006-2007) were set up. Linear mixed models with a random intercept term were fitted to the whole dataset (416 trees) for the three production periods. Clustered longitudinal mixed models, under a Bayesian approach with random terms related to intercept, time slope and nested effects, were fitted to a subset of the global dataset (9 plots and 76 trees), corresponding to the plots where production data for all trees in the three years were available. The selected models included, as independent variables, crown width, basal area per hectare, tree height and accumulated rainfall in the five+year periods, prio r to cone collection. Despite the small period considered in this study, the Bayesian analysis proved to be useful for calculations
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modelling spatial and temporal variability in a zero inflated variable the case of Stone Pine pinus Pinea l cone production
Ecological Modelling, 2011Co-Authors: Rafael Calama, Javier Gordo, Sven Mutke, Gregorio Montero, Jose Tome, Margarida TomeAbstract:Abstract Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone Pine (Pinus Pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of Stone Pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 Stone Pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in Stone Pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.
