Tree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines

Caballol, Maria; Ridley, Maia; Colangelo, Michele; Valeriano, Cristina; Camarero, J. Julio; Oliva, Jonàs

doi:10.1016/j.foreco.2021.119935

Cited by 11 publications

(5 citation statements)

References 41 publications

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“…However, it is important to consider that P. sylvestris can be more vulnerable to pathogens than P. halepensis and P. pinea in the studied forest. Caballol et al (2022) found that this species was more affected by Diplodia shoot blight than the rest of Pine species. We do not have information on previous hailstorms and subsequent Diplodia outbreaks that may explain P. sylvestris declining trends, but the greater sensitivity of the species to this pathogen and its low resilience capacity points to its vulnerability to climate change in sight of the importance of combined impacts of drought and pathogen attacks (McDowell et al, 2008(McDowell et al, , 2019Trugman et al, 2021).…”

Section: Discussionmentioning

confidence: 85%

“…However, important age differences between species makes difficult to assure that these results indicate that P. halepensis tolerates better current drought conditions in the region than P. pinea. Interestingly, Caballol et al (2022) found linkages between P. pinea defoliation and growth, indicating that those trees showing higher defoliation values grew less in the past. This may indicate that this species is suffering from drought-induced dieback and points to its drought vulnerability in the studied forests.…”

Section: Discussionmentioning

confidence: 98%

“…The studied stands were composed by mixed pine forests of P. sylvestris, P. nigra, P. pinea, and P. halepensis. In the year 2020, eight stands in the area were sampled for dendroecological purposes (Caballol et al, 2022). Two stem cores were taken at 1.3 m using Pressler increment borers (Haglöf, Sweden) for trees from the four pine species to reconstruct their growth patterns and estimate their age.…”

Section: Study Site and Climate Datamentioning

confidence: 99%

“…Sutton).) on the four co-occurring pine species (Caballol et al, 2022). We hypothesize that recent warming trends and the occurrence of severe droughts may have left an imprint in the radial growth series of those species offering valuable information to infer their vulnerability to water shortage.…”

Section: Introductionmentioning

confidence: 99%

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Mixed Pine Forests in a Hotter and Drier World: The Great Resilience to Drought of Aleppo Pine Benefits It Over Other Coexisting Pine Species

Gazol¹,

Oliva²,

Valeriano³

et al. 2022

Front. For. Glob. Change

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Drought is an important driver of forest dynamics in the Mediterranean region. The forecasted increase in drought frequency and severity can notably influence tree growth, forest structure, composition and productivity. Understanding how coexisting tree species respond to drought is thus crucial to understand which are less vulnerable and will perform better in a warmer and drier world. To assess drought vulnerability, we used dendrochronology to study the radial growth trends and responses to a drought index of four pine species (Pinus halepensis, Pinus pinea, Pinus nigra, and Pinus sylvestris) coexisting in North-eastern Spain. We reconstructed the growth of each species and evaluated their short- and long-term growth response to drought for the common period 1980–2017. The growth of the four pine species depended on water availability and high early spring temperatures impacted the growth of P. nigra and P. sylvestris negatively. The occurrence of a severe drought between 2005 and 2007 lead to marked growth reductions in the four species, but it was greater in magnitude in P. pinea and P. halepensis in 2005, and in P. nigra in 2007. The results of basal area increment models at the individual tree level suggested that P. halepensis trees grow more than the rest of species. After accounting for age and drought effects, P. nigra and P. sylvestris displayed negative growth trends in the 2008–2017 period while P. pinea and P. halepensis displayed positive growth trends. P. sylvestris was the most resistant species and P. pinea the less resistant. Conversely, P. halepensis and P. pinea were slightly more resilient than P. sylvestris. Moreover, P. sylvestris was the species displaying the highest autocorrelation and the lowest coefficient of variation in ring-width indices. A marked drop in the autocorrelation of P. pinea ring-width index was observed in response to the 2005 drought. These results indicate that all study species are vulnerable to drought but in different degrees. The strong resilience capacity of P. halepensis suggests that it will better thrive in a drier future, but mixed pine forests, such as the one here studied, may contract or become rare due to the strong sensitivity of P. pinea to drought and the lower post-drought performance of P. nigra and P. sylvestris.

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Section: Discussionmentioning

confidence: 85%

Section: Discussionmentioning

confidence: 98%

Section: Study Site and Climate Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mixed Pine Forests in a Hotter and Drier World: The Great Resilience to Drought of Aleppo Pine Benefits It Over Other Coexisting Pine Species

Gazol¹,

Oliva²,

Valeriano³

et al. 2022

Front. For. Glob. Change

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“…The molecular data presented here suggest that S. sapinea might be more often the cause of shoot blight in Pinus sylvestris than in other pine species, in which it could be more often a secondary colonizer. A recent study shows that infected P. sylvestris trees are more likely to die from S. sapinea infection than trees from P. nigra, P. pinea or P. halepensis (Caballol et al, 2022). Different pathogens have different infection approaches, as observed with the multiple patterns of hyphal colonization on needles: for example, the fungus Rhizoctonia solani, infecting and causing maize sheath blight, can penetrate through the leaf epidermis and stomata (Jie et al, 2000).…”

Section: Discussionmentioning

confidence: 99%

Host and abiotic constraints on the distribution of the pine fungal pathogen Sphaeropsis sapinea (= Diplodia sapinea)

Roy¹,

Kyritsi²,

Reinwarth³

et al. 2022

Front. For. Glob. Change

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Plant fungal pathogens are an increasing emerging threat as climate change progresses. Sphaeropsis sapinea (syn. Diplodia sapinea), the causal fungal agent of Diplodia tip blight, is a major pathogen of pines of forestry and ornamental relevance in Europe and worldwide. Here, we combined molecular-based field surveys in a common-garden setting and across an elevation gradient with historical records, cultivation-based growth experiments and microscopy to report on host and abiotic constraints on the distribution of S. sapinea. Using the arboretum at the Botanical Garden Berlin, Germany, to control for environmental variability, S. sapinea was detected on all seven host Pinus species we studied. However, P. sylvestris is the only species in which the fungus was detected in symptomless needles at the arboretum, and the most frequently recorded host for over a century, suggesting that it is the main, and perhaps, potential original host. In addition, sampling symptomatic needles in four out of the seven same species across a gradient from 200 to 2,100 m of elevation in the French Alps, S. sapinea was not detected at elevation higher than 800 m. Abiotic constraints were also supported by reduced growth of isolates of S. sapinea at low temperature under controlled conditions, but a 35°C prior stress exposure increased the subsequent growth of S. sapinea within its optimal temperature range (20-30°C). Altogether, our study thus not only suggests that S. sapinea is more likely to cause tip blight in P. sylvestris compared to the other species we studied, but also that in the current context of global climate change with predicted temperature increases, the fungus could infect a wider range of pine hosts and locations worldwide.

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Using machine learning algorithms to cluster and classify stone pine (Pinus pinea L.) populations based on seed and seedling characteristics

Caliskan,

Kartal,

Balekoglu

et al. 2024

Eur J Forest Res

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The phenotype of a woody plant represents its unique morphological properties. Population discrimination and individual classification are crucial for breeding populations and conserving genetic diversity. Machine Learning (ML) algorithms are gaining traction as powerful tools for predicting phenotypes. The present study is focused on classifying and clustering the seeds and seedlings in terms of morphological characteristics using ML algorithms. In addition, the k-means algorithm is used to determine the ideal number of clusters. The results obtained from the k-means algorithm were then compared with reality. The best classification performance achieved by the Random Forest algorithm was an accuracy of 0.648 and an F1-Score of 0.658 for the seed traits. Also, the best classification performance for stone pine seedlings was observed for the k-Nearest Neighbors algorithm (k = 18), for which the accuracy and F1-Score were 0.571 and 0.582, respectively. The best clustering performance was achieved with k = 2 for the seed (average Silhouette index = 0.48) and seedling (average Silhouette Index = 0.51) traits. According to the principal component analysis, two dimensions accounted for 97% and 63% of the traits of seeds and seedlings, respectively. The most important features between the seed and seedling traits were cone weight and bud set, respectively. This study will provide a foundation and motivation for future efforts in forest management practices, particularly regarding reforestation, yield optimization, and breeding programs.

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Tree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines

Cited by 11 publications

References 41 publications

Mixed Pine Forests in a Hotter and Drier World: The Great Resilience to Drought of Aleppo Pine Benefits It Over Other Coexisting Pine Species

Mixed Pine Forests in a Hotter and Drier World: The Great Resilience to Drought of Aleppo Pine Benefits It Over Other Coexisting Pine Species

Host and abiotic constraints on the distribution of the pine fungal pathogen Sphaeropsis sapinea (= Diplodia sapinea)

Using machine learning algorithms to cluster and classify stone pine (Pinus pinea L.) populations based on seed and seedling characteristics

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