Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data

Machine-learning algorithms have gained popularity in recent years in the field of ecological modeling due to their promising results in predictive performance of classification problems. While the application of such algorithms has been highly simplified in the last years due to their well-documented integration in commonly used statistical programming languages such as R, there are several practical challenges in the field of ecological modeling related to unbiased performance estimation, optimization of algorithms using hyperparameter tuning and spatial autocorrelation. We address these issues in the comparison of several widely used machine-learning algorithms such as Boosted Regression Trees (BRT), k-Nearest Neighbor (WKNN), Random Forest (RF) and Support Vector Machine (SVM) to traditional parametric algorithms such as logistic regression (GLM) and semi-parametric ones like generalized additive models (GAM). Different nested cross-validation methods including hyperparameter tuning methods are used to evaluate model performances with the aim to receive bias-reduced performance estimates. As a case study the spatial distribution of forest disease Diplodia sapinea in the Basque Country in Spain is investigated using common environmental variables such as temperature, precipitation, soil or lithology as predictors. Results show that GAM and RF (mean AUROC estimates 0.708 and 0.699) outperform all other methods in predictive accuracy. The effect of hyperparameter tuning saturates at around 50 iterations for this data set. The AUROC differences between the bias-reduced (spatial cross-validation) and overoptimistic (non-spatial cross-validation) performance estimates of the GAM and RF are 0.167 (24%) and 0.213 (30%), respectively. It is recommended to also use spatial partitioning for cross-validation hyperparameter tuning of spatial data

Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data

Machine-learning algorithms have gained popularity in recent years in the field of ecological modeling due to their promising results in predictive performance of classification problems. While the application of such algorithms has been highly simplified in the last years due to their well-documented integration in commonly used statistical programming languages such as R, there are several practical challenges in the field of ecological modeling related to unbiased performance estimation, optimization of algorithms using hyperparameter tuning and spatial autocorrelation. We address these issues in the comparison of several widely used machine-learning algorithms such as Boosted Regression Trees (BRT), kNearest Neighbor (WKNN), Random Forest (RF) and Support Vector Machine (SVM) to traditional parametric algorithms such as logistic regression (GLM) and semi-parametric ones like Generalized Additive Models (GAM). Different nested cross-validation methods including hyperparameter tuning methods are used to evaluate model performances with the aim to receive bias-reduced performance estimates. As a case study the spatial distribution of forest disease (Diplodia sapinea) in the Basque Country in Spain is investigated using common environmental variables such as temperature, precipitation, soil or lithology as predictors. Results show that GAM and Random Forest (RF) (mean AUROC estimates 0.708 and 0.699) outperform all other methods in predictive accuracy. The effect of hyperparameter tuning saturates at around 50 iterations for this data set. The AUROC differences between the bias-reduced (spatial cross-validation) and overoptimistic (non-spatial cross-validation) performance estimates of the GAM and RF are 0.167 (24%) and 0.213 (30%), respectively. It is recommended to also use spatial partitioning for cross-validation hyperparameter tuning of spatial data. The models developed in this study enhance the detection of Diplodia sapinea in the Basque Country compared to previous studies

The transcriptome of Pinus pinaster under Fusarium circinatum challenge

Additional file 1 Symptoms at the shoot tip of inoculated (left side) and mock-inoculated (right side) Pinus pinaster seedlings by the end of the experiment (33 dpi).Additional file 2. Statistics for each TransABySS and Trinity assembly. N seq: number of transcripts; N bases: number of bases; Mean length: mean length of the transcripts; N50: N50 value; Ns: number of unknown bases; % GC: guanine and cytosine content; trinity-N: in silico normalized trinity assembly; trinity-nN: non-normalized trinity assemblies. * Best quality preliminary assemblies selected to generate the final assembly.Additional file 3. Comparative statistics between normalized (Norm) and non-normalized (N-norm) Trinity preliminary assemblies. Kmer value; % of mapped fragments; % of good mapping; AS: assembly score; OP: optimal score; OC: optimal cutoff; Number of good contigs; % good contigs.Additional file 4. BUSCO analysis against the embryophyta lineage database comparing the last Pinus de novo transcriptomes published. P. patula v1.0 [110]; P. patula v2.0 and P. tecunumanii [108].Additional file 5. Pinus pinaster de novo transcriptome annotation.Additional file 6. Pinus pinaster de novo transcriptome annotation by Mercator tool.Additional file 7. mapped reads for each species. Number of differential expressed (DE) genes for Pinus pinaster and DE genes for Fusarium circinatum at each time point in inoculated samples (FDR 0.5). Ppin: P. pinaster; Fcir: F. circinatum;HC: high confident.Additional file 8. Principal component analyses (PCA) for Pinus pinaster (above) and Fusarium circinatum (below) rlog data of the differential expression gene analysis (DESeq2). In red: mock-inoculated samples; in blue: inoculated samples at 3 dpi; in green: inoculated samples at 5 dpi; in yellow: inoculated samples at 10 dpi.Additional file 9. Clustering of Pinus pinaster and Fusarium circinatum differential expressed (DE) genes. For each cluster with gene ontology (GO) enriched terms, number of genes and percentage for genes are indicated.Additional file 10. Significantly enriched GO terms identified from Pinus pinaster genes in each cluster.Additional file 11: Phytohormone related differentially expressed (DE) genes in Pinus pinaster.Additional file 12: Pathogenesis related (PR) genes differentially expressed (DE) in Pinus pinaster.Additional file 13: Significantly enriched GO terms identified from high confidence expressed Fusarium circinatum genes.Additional file 14: Hormone related differential expressed (DE) genes in Fusarium circinatum.Additional file 15: Fusarium circinatum DE genes related to hormone production with hits in the Pathogen Host Interaction (PHI) database.Additional file 16:. RNA-seq data statistics for each sample at each time point, before and after filtering and trimming. Dpi: days post-inoculation; BR: biological replicate, RIN: RNA Integrity Number; Q 30: Phred quality score 30.BACKGROUND : Fusarium circinatum, the causal agent of pitch canker disease, poses a serious threat to several Pinus species affecting plantations and nurseries. Although Pinus pinaster has shown moderate resistance to F. circinatum, the molecular mechanisms of defense in this host are still unknown. Phytohormones produced by the plant and by the pathogen are known to play a crucial role in determining the outcome of plant-pathogen interactions. Therefore, the aim of this study was to determine the role of phytohormones in F. circinatum virulence, that compromise host resistance. RESULTS : A high quality P. pinaster de novo transcriptome assembly was generated, represented by 24,375 sequences from which 17,593 were full length genes, and utilized to determine the expression profiles of both organisms during the infection process at 3, 5 and 10 days post-inoculation using a dual RNA-sequencing approach. The moderate resistance shown by Pinus pinaster at the early time points may be explained by the expression profiles pertaining to early recognition of the pathogen, the induction of pathogenesis-related proteins and the activation of complex phytohormone signaling pathways that involves crosstalk between salicylic acid, jasmonic acid, ethylene and possibly auxins. Moreover, the expression of F. circinatum genes related to hormone biosynthesis suggests manipulation of the host phytohormone balance to its own benefit. CONCLUSIONS : We hypothesize three key steps of host manipulation: perturbing ethylene homeostasis by fungal expression of genes related to ethylene biosynthesis, blocking jasmonic acid signaling by coronatine insensitive 1 (COI1) suppression, and preventing salicylic acid biosynthesis from the chorismate pathway by the synthesis of isochorismatase family hydrolase (ICSH) genes. These results warrant further testing in F. circinatum mutants to confirm the mechanism behind perturbing host phytohormone homeostasis.Laura Hernández was supported by a fellowship from INIA (FPI-INIA) and additional funding for a Short-Term Scientific Mission in the Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa, was provided by Pinestrength Cost Action (FP1406). Financial support for this research was provided by project RTA 2017–00063-C04–01 (Programa Estatal I + D + i, INIA, Spain). EAV was supported through the Technology Innovation Agency (TIA) South Africa, Forest Molecular Genetics Cluster Program. SN was supported by the National Research Foundation (NRF) of South Africa, Y-rated grant program.https://bmcgenomics.biomedcentral.comam2020BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant Patholog

Root infection of canker pathogens, Fusarium circinatum and Diplodia sapinea, in asymptomatic trees in Pinus radiata and Pinus pinaster plantations

[EN] The existence of a latent stage within host tissue of the pine pathogens Fusarium circinatum and Diplodia sapinea, the causal agents of pitch canker and shoot blight disease respectively, has previously been cited. However, studies on this cryptic phase in each disease lifecycle has only been focused on the host aerial parts but not on the roots. Therefore, our objective was to analyze the presence of both pathogens in roots of non-symptomatic mature trees in plantations where the pathogens are known to be causing canker symptoms. For that, we sampled roots from ten non-symptomatic and ten symptomatic trees in three Pinus radiata and one Pinus pinaster plantations in Basque Country, Spain. Both pathogens were isolated from roots of non-symptomatic trees in a higher frequency than from roots of symptomatic trees, 23.3% and 6.6% respectively for D. sapinea and 16.6% and 3.3% respectively for F. circinatum. Neither pathogens was detected in the P. pinaster plantation. The two pathogens were never isolated from the same tree. A high molecular variability was observed for D. sapinea isolates with six different haplotypes and two mating types for the eleven characterized isolates, but only one haplotype and mating type was found for F. circinatum, with all isolates of both fungi being proved pathogenic. These results evidence the importance root infection may have in the disease lifecycle and, therefore, disease management.We acknowledge Maria Teresa Morales Clemente for her excellent technical assistance. Laura Hernandez-Escribano was supported by a fellowship from INIA (FPI-INIA). Financial support for this research was provided by project RTA2013-00048-C03-01, RTA2017-00063-C04-01 and C04-03 (National Progamme I + D + I, INIA, Spain) and the Project Healthy Forest LIFE14 ENV/ES/000179. 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Sources of Diplodia pinea endophytic infections in Pinus patula and P. radiata seedlings in South Africa. Forest Pathology, 41(5), 370-375. doi:10.1111/j.1439-0329.2010.00691.xFABRE, B., PIOU, D., DESPREZ-LOUSTAU, M.-L., & MARÇAIS, B. (2011). Can the emergence of pine Diplodia shoot blight in France be explained by changes in pathogen pressure linked to climate change? Global Change Biology, 17(10), 3218-3227. doi:10.1111/j.1365-2486.2011.02428.xSwett, C. L., Kirkpatrick, S. C., & Gordon, T. R. (2016). Evidence for a Hemibiotrophic Association of the Pitch Canker Pathogen Fusarium circinatum with Pinus radiata. Plant Disease, 100(1), 79-84. doi:10.1094/pdis-03-15-0270-reMartín-Rodrigues, N., Sanchez-Zabala, J., Salcedo, I., Majada, J., González-Murua, C., & Duñabeitia, M. K. (2015). New insights into radiata pine seedling root infection byFusarium circinatum. Plant Pathology, 64(6), 1336-1348. doi:10.1111/ppa.12376Swett, C. L., & Gordon, T. R. (2016). 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A simplified method for identifying Fusarium spp. occurring on wheat. Canadian Journal of Botany, 59(9), 1599-1609. doi:10.1139/b81-217Slippers, B., Crous, P. W., Denman, S., Coutinho, T. A., Wingfield, B. D., & Wingfield, M. J. (2004). Combined multiple gene genealogies and phenotypic characters differentiate several species previously identified asBotryosphaeria dothidea. Mycologia, 96(1), 83-101. doi:10.1080/15572536.2005.11833000Alves, A., Linaldeddu, B. T., Deidda, A., Scanu, B., & Phillips, A. J. L. (2014). The complex of Diplodia species associated with Fraxinus and some other woody hosts in Italy and Portugal. Fungal Diversity, 67(1), 143-156. doi:10.1007/s13225-014-0282-9Hyde, K. D., Nilsson, R. H., Alias, S. A., Ariyawansa, H. A., Blair, J. E., Cai, L., … Zhou, N. (2014). One stop shop: backbones trees for important phytopathogenic genera: I (2014). Fungal Diversity, 67(1), 21-125. doi:10.1007/s13225-014-0298-1Dissanayake, A. (2016). 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A Species-Specific PCR Assay for Detection of Diplodia pinea and D. scrobiculata in Dead Red and Jack Pines with Collar Rot Symptoms. Plant Disease, 90(3), 307-313. doi:10.1094/pd-90-0307Schweigkofler, W., O’Donnell, K., & Garbelotto, M. (2004). Detection and Quantification of Airborne Conidia of Fusarium circinatum, the Causal Agent of Pine Pitch Canker, from Two California Sites by Using a Real-Time PCR Approach Combined with a Simple Spore Trapping Method. Applied and Environmental Microbiology, 70(6), 3512-3520. doi:10.1128/aem.70.6.3512-3520.2004Wallace, M. M., & Covert, S. F. (2000). Molecular Mating Type Assay forFusarium circinatum. Applied and Environmental Microbiology, 66(12), 5506-5508. doi:10.1128/aem.66.12.5506-5508.2000Berbegal, M., Pérez-Sierra, A., Armengol, J., & Grünwald, N. J. (2013). Evidence for Multiple Introductions and Clonality in Spanish Populations of Fusarium circinatum. Phytopathology®, 103(8), 851-861. doi:10.1094/phyto-11-12-0281-rIturritxa, E., Ganley, R. J., Wright, J., Heppe, E., Steenkamp, E. T., Gordon, T. R., & Wingfield, M. J. (2011). A genetically homogenous population of Fusarium circinatum causes pitch canker of Pinus radiata in the Basque Country, Spain. Fungal Biology, 115(3), 288-295. doi:10.1016/j.funbio.2010.12.014Elvira-Recuenco, M., Iturritxa, E., Majada, J., Alia, R., & Raposo, R. (2014). Adaptive Potential of Maritime Pine (Pinus pinaster) Populations to the Emerging Pitch Canker Pathogen, Fusarium circinatum. PLoS ONE, 9(12), e114971. doi:10.1371/journal.pone.0114971Garbelotto, M., Smith, T., & Schweigkofler, W. (2008). Variation in Rates of Spore Deposition of Fusarium circinatum, the Causal Agent of Pine Pitch Canker, Over a 12-Month-Period at Two Locations in Northern California. Phytopathology®, 98(1), 137-143. doi:10.1094/phyto-98-1-0137Serra-Varela, M. J., Alía, R., Pórtoles, J., Gonzalo, J., Soliño, M., Grivet, D., & Raposo, R. (2017). Incorporating exposure to pitch canker disease to support management decisions of Pinus pinaster Ait. in the face of climate change. PLOS ONE, 12(2), e0171549. doi:10.1371/journal.pone.0171549Hernandez-Escribano, L., Iturritxa, E., Elvira-Recuenco, M., Berbegal, M., Campos, J. A., Renobales, G., … Raposo, R. (2018). Herbaceous plants in the understory of a pitch canker-affected Pinus radiata plantation are endophytically infected with Fusarium circinatum. Fungal Ecology, 32, 65-71. doi:10.1016/j.funeco.2017.12.001Smith, H., Wingfield, M. J., Coutinho, T. A., & Crous, P. W. (1996). Sphaeropsis sapinea and Botryosphaeria dothidea endophytic in Pinus spp. and Eucalyptus spp. in South Africa. South African Journal of Botany, 62(2), 86-88. doi:10.1016/s0254-6299(15)30596-2Santini, A., Pepori, A., Ghelardini, L., & Capretti, P. (2008). Persistence of some pine pathogens in coarse woody debris and cones in a Pinus pinea forest. Forest Ecology and Management, 256(3), 502-506. doi:10.1016/j.foreco.2008.05.010Oblinger, B. W., Smith, D. R., & Stanosz, G. R. (2011). Red pine harvest debris as a potential source of inoculum of Diplodia shoot blight pathogens. Forest Ecology and Management, 262(4), 663-670. doi:10.1016/j.foreco.2011.04.038Eyles, A., Bonello, P., Ganley, R., & Mohammed, C. (2009). Induced resistance to pests and pathogens in trees. New Phytologist, 185(4), 893-908. doi:10.1111/j.1469-8137.2009.03127.xJunker, C., Draeger, S., & Schulz, B. (2012). A fine line – endophytes or pathogens in Arabidopsis thaliana. Fungal Ecology, 5(6), 657-662. doi:10.1016/j.funeco.2012.05.002Flowers, J. L., Hartman, J. R., & Vaillancourt, L. J. (2006). Histology of Diplodia pinea in diseased and latently infected Pinus nigra shoots. Forest Pathology, 36(6), 447-459. doi:10.1111/j.1439-0329.2006.00473.

Weather Variables Associated with Spore Dispersal of Lecanosticta acicola Causing Pine Needle Blight in Northern Spain

In the last decade, the impact of needle blight fungal pathogens on the health status of forests in northern Spain has marked a turning point in forest production systems based on Pinus radiata species. Dothistroma needle blight caused by Dothistroma septosporum and D. pini, and brown spot needle blight caused by Lecanosticta acicola, coexist in these ecosystems. There is a clear dominance of L. acicola with respect to the other two pathogens and evidence of sexual reproduction in the area. Understanding L. acicola spore dispersal dynamics within climatic determinants is necessary to establish more efficient management strategies to increase the sustainability of forest ecosystems. In this study, spore counts of 15 spore traps placed in Pinus ecosystems were recorded in 2019 and spore abundance dependency on weather data was analysed using generalised additive models. During the collection period, the model that best fit the number of trapped spores included the daily maximum temperature and daily cumulative precipitation, which was associated to higher spore counts. The presence of conidia was detected from January and maximum peaks of spore dispersal were generally observed from September to November.This research was funded by the Spanish Ministry of Science and INIA, grant number: RTA 2017-00063-C04-03, LIFE programme, grant number: LIFE14 ENV/ES/000179 and by the Department of Economic Development, Sustainability and Environment (Basque Government), grant reference: FUNGITRAP2019.S

Comparison of Diplodia Tip Blight Pathogens in Spanish and North American Pine Ecosystems

[EN] Diplodia tip blight is the most ubiquitous and abundant disease in Spanish Pinus radiata plantations. The economic losses in forest stands can be very severe because of its abundance in cones and seeds together with the low genetic diversity of the host. Pinus resinosa is not genetically diverse in North America either, and Diplodia shoot blight is a common disease. Disease control may require management designs to be adapted for each region. The genetic diversity of the pathogen could be an indicator of its virulence and spreading capacity. Our objective was to understand the diversity of Diplodia spp. in Spanish plantations and to compare it with the structure of American populations to collaborate in future management guidelines. Genotypic diversity was investigated using microsatellite markers. Eight loci (SS9-SS16) were polymorphic for the 322 isolates genotyped. The results indicate that Diplodia sapinea is the most frequent Diplodia species present in plantations of the north of Spain and has high genetic diversity. The higher genetic diversity recorded in Spain in comparison to previous studies could be influenced by the intensity of the sampling and the evidence about the remarkable influence of the sample type.This research was funded by INIA, grant number: RTA 2017-00063-C04-03, LIFE programme, grant number: LIFE14 ENV/ES/000179 and by the Basque Government, grant number FUNGITRAP 19-00031. Red pine cone collection in New England and pathogen isolation was funded by USDA Forest Service.Aragonés, A.; Manzanos, T.; Stanosz, G.; Munck, IA.; Raposo, R.; Elvira-Recuenco, M.; Berbegal Martinez, M.... (2021). Comparison of Diplodia Tip Blight Pathogens in Spanish and North American Pine Ecosystems. Microorganisms. 9(12):1-17. https://doi.org/10.3390/microorganisms9122565S11791

Global Geographic Distribution and Host Range of Fusarium circinatum, the Causal Agent of Pine Pitch Canker

Funding: This study was financially supported by COST Action FP1406 (PINESTRENGTH), the Estonian Science Foundation grant PSG136, the Forestry Commission, United Kingdom, the Phytophthora Research Centre Reg. No. CZ.02.1.01/0.0/0.0/15_003/0000453, a project co-financed by the European Regional Development Fund. ANSES is supported by a grant managed by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” programme (ANR-11-LABX-0002-01, Laboratory of ExcellenceARBRE). SW was partly supported by BBSRC Grant reference BB/L012251/1 “Promoting resilience of UK tree species to novel pests & pathogens: ecological & evolutionary solutions (PROTREE)” jointly funded by BBSRC, Defra, ESRC, the Forestry Commission, NERC and the Scottish Government, under the Tree Health and Plant Biosecurity Initiative. Annual surveys in Switzerland were financially supported by the Swiss Federal Office for the Environment FOEN. Acknowledgments: Andrea Kunova and Cristina Pizzatti are acknowledged for the assistance in the sampling. Thanks are due to Dina Ribeiro and Helena Marques from ICNF-Portuguese Forest Authority for providing location coordinates. We thank three anonymous reviwers for valuable corrections and suggestions.Peer reviewedPublisher PD