Morphological Differences in Pinus strobiformis Across Latitudinal and Elevational Gradients

Leal‐Sàenz, Alejandro; Waring, Kristen M.; Menon, Mitra; Cushman, Samuel A.; Eckert, Andrew J.; Flores‐Rentería, Lluvia; Hernández-Díaz, José Ciro; López-Sánchez, Carlos A.; Martínez-Guerrero, José Hugo; Wehenkel, Christian

doi:10.3389/fpls.2020.559697

Cited by 15 publications

(21 citation statements)

References 96 publications

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“…(Multiple) Linear regression is one of the simplest machine learning algorithms, often used for comparison purposes and creating parametric regression equations based on two (or more) parameters (Leal-Sáenz et al, 2020 ). A non-parametric Random Forest regression is based on constructing several decision trees at training time and outputting the average of the classes as the prediction of all individual trees (Breiman, 2001 ).…”

Section: Methodsmentioning

confidence: 99%

“…We used Random Forests and Neural Networks because they have previously been applied in analysis of forest damages, and they have been found to perform better for events (especially in forestry) than other statistical methods (Hanewinkel, 2005 ; Guo et al, 2016 ). These seven algorithms were also successful to predict seed and cone traits of P. strobifomis by environmental variables (Leal-Sáenz et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

“…Conserving these pine species and their genetic diversity is therefore of great ecological importance (Bower et al, 2011 ). P. strobiformis is the most widespread of the white pines in Mexico and is widely distributed throughout the mountains of northern Mexico, from northern Chihuahua to the state of Jalisco in the south (Shirk et al, 2018 ; Leal-Sáenz et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Assessment and Models of Insect Damage to Cones and Seeds of Pinus strobiformis in the Sierra Madre Occidental, Mexico

et al. 2021

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Insect damage to cones and seeds has a strong impact on the regeneration of conifer forest ecosystems, with broader implications for ecological and economic services. Lack of control of insect populations can lead to important economic and environmental losses. Pinus strobiformis is the most widespread of the white pines in Mexico and is widely distributed throughout the mountains of northern Mexico. Relatively few studies have examined insect damage to the cones and seeds of these pines, especially in Mexico. In this study, we therefore analyzed insect damage to cones and seeds of P. strobiformis in Mexico by using X-ray and stereomicroscopic analysis. The specific objectives of the study were (a) to characterize insect damage by measuring external and internal cone traits, (b) to assess the health of seeds and cones of P. strobiformis in the Sierra Madre Occidental, Mexico, and (c) to estimate the relative importance of the effects of different environmental variables on cone and seed damage caused by insects. We found that 80% of P. strobiformis seeds and 100% of the tree populations studied had damage caused by insects. Most seeds were affected by Leptoglossus occidentalis, Tetyra bipunctata, Megastigmus albifrons, and the Lepidoptera complex (which includes Apolychrosis synchysis, Cydia latisigna, Eucosma bobana, and Dioryctria abietivorella). The cones of all tree populations were affected by some type of insect damage, with Lepidoptera causing most of the damage (72%), followed by Conophthorus ponderosae (15%), the hemipteran L. occidentalis (7%), and the wasp M. albifrons (6%). The proportion of incomplete seeds in P. strobiformis at the tree level, cone damage by M. albifrons and seed damage in L. occidentalis were associated with various climate and soil variables and with crown dieback. Thus, cone and seed insect damage can be severe and potentially impact seed production in P. strobiformis and the reforestation potential of the species. The study findings will enable managers to better identify insects that cause damage to cone and seeds. In addition, identification of factors associated with damage may be useful for predicting the levels of insect predation on seeds and cones.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment and Models of Insect Damage to Cones and Seeds of Pinus strobiformis in the Sierra Madre Occidental, Mexico

et al. 2021

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“…We selected no-collinear environmental variables (|r| < 0.7) that were significantly correlated to the relative frequency (f r ) of outlier loci (C) for modelling six species-specific machine learning algorithms (MLM) of f r , all including cross-validation (CV). We used the following methods: (i) linear regression ("lm"), (ii) Random Forest ("rf"), (iii) Neural Network ("nnet"), iv) Model Averaged Neural Network ("avNNet"), (v) Multi-Layer Perceptron ("mlpWeightDecay") and (vi) Bayesian Regularized Neural Networks ("brnn") [64,65] (Available online: http://topepo.github.io/caret/index.html (accessed on December 2020)) in R (version 3.3.4) [63] (see more in [11]). Models were tested 15 through 10-fold crossvalidation, by using 80% of the dataset as a training set and the remaining 20% as a test set.…”

Section: Modelling Seed Zones From Environmentally-associated Aflp Variants and Environmental Factorsmentioning

confidence: 99%

“…Seed zones can be delineated: (i) by conducting provenance trials to detect associations between genetic, geographic and climatic factors [8][9][10]; (ii) by correlating climate and geomorphological data; and (iii) by using climate surrogates, such as latitude, longitude and/or elevation [5]; with the risk that such variables are not always good phenotype predictors for widespread tree species (e.g., [11]). Provenance trials are however timeconsuming and usually only allow measuring phenotypic differences between individuals and populations under common conditions.…”

Section: Introductionmentioning

confidence: 99%

Modelling Shifts and Contraction of Seed Zones in Two Mexican Pine Species by Using Molecular Markers

Simental‐Rodriguez

Pérez-Luna

Hernández-Díaz

et al. 2021

Forests

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A seed zone or provenance region is an area within which plants can be moved with little risk of maladaptation because of the low environmental variation. Delineation of seed zones is of great importance for commercial plantations and reforestation and restoration programs. In this study, we used AFLP markers associated with environmental variation for locating and delimiting seed zones for two widespread and economically important Mexican pine species (Pinus arizonica Engelm. and P. durangensis Martínez), both based on recent climate conditions and under a predicted climate scenario for 2030 (Representative Concentration Pathway of ~4.5 Wm−2). We expected to observe: (i) associations between seed zones and local climate, soil and geographical factors, and (ii) a meaning latitudinal shift of seed zones, along with a contraction of species distributions for the period 1990–2030 in a northward direction. Some AFLP outliers were significantly associated with spring and winter precipitation, and with phosphorus concentration in the soil. According to the scenario for 2030, the estimated species and seed zone distributions will change both in size and position. Our modeling of seed zones could contribute to reducing the probabilities of maladaptation of future reforestations and plantations with the pine species studied.

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Effects of geo‐climate factors on phenotypic variation in cone and seed traits of Pinus yunnanensis

Gao,

Liu,

Miao

et al. 2023

Ecology and Evolution

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Evaluating variations in reproductive traits and the response of the variations to geo‐climate conditions are essential for understanding the persistence, evolution, and range dynamics of plant populations. However, there are insufficient studies to attempt to analyze the importance of geo‐climate factors in explaining within‐ or among‐population variation in reproductive traits. We examined 14 traits for 2671 cones of Pinus yunnanensis collected from nine populations in the mountains of Southwest China to characterize the patterns of phenotypic variation of traits and estimate environmental effects on these trait performances and trait variation. We found the contribution of intrapopulation variation to the overall variation was greater than the interpopulation variation and the larger coefficients of variation for the populations lying at the edge of northern and southern regions. Climatic variables are more important than geographical and tree size variables in their relationships to cone and seed traits. Populations in more humid and warmer climate expressed greater cone and seed weight and seed number but lower seed abortion rate, while the larger coefficients of variation in seed weight and number were detected in northern and southern marginal regions with drier or colder climate. Our study illustrates that intraspecific trait variation should be considered when examining plant species response to changing climate and suggests that the high variability rather than high quality of seed traits in the marginal regions with drier or colder climate might foster plant‐population persistence in stressful conditions.

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Morphological Differences in Pinus strobiformis Across Latitudinal and Elevational Gradients

Cited by 15 publications

References 96 publications

Assessment and Models of Insect Damage to Cones and Seeds of Pinus strobiformis in the Sierra Madre Occidental, Mexico

Assessment and Models of Insect Damage to Cones and Seeds of Pinus strobiformis in the Sierra Madre Occidental, Mexico

Modelling Shifts and Contraction of Seed Zones in Two Mexican Pine Species by Using Molecular Markers

Effects of geo‐climate factors on phenotypic variation in cone and seed traits of Pinus yunnanensis

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