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Enregistrement W6986899888

Re-utilizing forest genetic trials to inform reforestation during a time of rapid climate change

2024· dissertation· en· W6986899888 sur OpenAlexaboutno aff

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetic diversity and population structure
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésReforestationClimate changeForest managementRange (aeronautics)PopulationLocal adaptationForest ecologyBasal areaBeech
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

European forest ecosystems are changing drastically. The accelerating speed of current climate warming, further paired with drought events, storms and insect calamities, already results in reduced fitness, changes in forest health, species composition and productivity. Forest management is committed to develop suitable adaptation strategies to maintain the multitude of ecosystem services. In this context, the choice of seed origin for forest conversion and reforestation represents a key question to their success. Provenance trials, that test a wide range of provenances planted across multiple test sites, provide the urgently required evidence of population specific response to variable environmental conditions and may be used to derive recommendations under future conditions. This thesis concentrates on two economically and ecologically important native tree species, European beech and Norway spruce, as well as one of the most common introduced broadleaf species, Northern red oak. It provides a comprehensive analysis of their adaptive population differentiation and ability of phenotypically plastic response. For beech, 85 range-wide provenances were observed for 25 years in western, northern and eastern Germany. Considerable provenance differentiation exists, explaining 21% (stem form) to 45% (basal area) of the variance at individual sites and 20 to 39% across sites, while interactions between provenance and environment were absent. At the landscape level, spatially neighboring provenances showed similar trait expressions. These patterns were similar for height and basal area, but different for stem form. They could be directly linked to geographical variables using a multivariate regression tree analysis, which captured 58% of the phenotypic variation, whereby eleven ‘ecotypes’ characterized by local adaptation were delineated. A selection by two multi-trait indices gave highly concordant results and further underlined the trade-off between growth and stem form. Overall, the intermediate elevations of the central highlands in western Germany host highly suitable provenances. Lower elevation provenances from the southeast adapted to continental climate with harsh and cold winters, but warm and dry summers profit from the transfer to the favorable growing conditions in Germany and represent potential candidates for assisted migration. For red oak, each six provenances sourced from German stands and from North America were examined at age 33 on sites in northern, eastern and central Germany. In contrast to beech, provenance by environment interactions were significant and the thorough investigation of their nature provided highly consistent results. German provenances were mostly superior. This was particularly prevalent at the Atlantic site in Schleswig-Holstein, where the most outstanding provenance yields a basal area sum per hectare of +130% compared to the mean across six American provenances. Four of six German provenances were categorized as productive generalists, being suitable for planting across environments, while the other two are productive specialists for humid sites. Provenances from the native range had a lower performance, despite for the driest environment in eastern Germany, where one Canadian provenance sourced north of the Great Lakes emerged as a suitable specialist. Provenances from higher elevations in Georgia and Tennessee grew poorly and had low survival rates, especially in Schleswig-Holstein. Growth performance and survival of spruce was investigated based on the most extensive provenance trial series worldwide, established to test 1,100 provenances in 13 European countries. The analysis of 33 German sites of 100 provenances each, summarized to ten aggregated provenance groups, revealed relatively consistent ranks between groups up to age 51. Provenances from the Hercyno-Carpathian domain had superior short-term and positive long-term growth, while those towards the northern and southern range limits performed poorly. To develop a universal response function, the data set was extended to a total of 97 sites with 100 provenances each. Increasing summer heat paired with decreasing water availability was identified as the main climatic variable that restricts growth, while a prolonged frost-free period enables a longer period of active growth and therefore increasing growth potential within the restricted, remaining area. Clear signals of local adaptation to climatic clines spanning the entire range are barely detectable, as they are disguised by a latitudinal cline. This cline strongly reflects population differentiation for the Baltic domain, but fails to capture the high phenotypic variation associated to the geographic heterogeneity in the Central European Mountain ranges paired with the species history of postglacial migration. Finally, growth predictions of the trait-based model were compared to the predictions of a classic occurrence-based species distribution model. Both models showed a substantial retreat towards the northern latitudes and higher elevations (-55% and -43% by the 2080s). However, thanks to the species’ particularly high phenotypic plasticity the decline is delayed. Model-based prescriptions for assisted migration may not decrease the predicted range decline for Norway spruce, but may help to capitalize on potential opportunities associated with warming climate in the remaining area.:1 General introduction 1.1 European forests under climate pressure 1.2 The capacity of natural populations to cope with changing conditions and its limits 1.3 Strategies of adaptive forest management 1.4 Provenance trials to study population response 1.5 The theory of local optimality and its significance for seed deployment 1.6 Thesis outline and objectives 1.7 Species of interest and experimental data basis 1.8 The analytical tool set 1.9 Author contributions 2 Ecotypic variation in multiple traits of European beech: selection of suitable provenances based on performance and stability 2.1 Abstract 2.2 Introduction 2.3 Material and Methods 2.3.1 Experimental design 2.3.2 Measurement of traits 2.3.3 Quantification of provenance and site effects 2.3.4 Spatial interpolation of trait variation 2.3.5 Multi-variate grouping of provenances 2.3.6 Calculation of multi-trait indices for provenance selection 2.4 Results 2.4.1 Differentiation among provenances at individual sites 2.4.2 Provenance by environment interactions 2.4.3 Spatial patterns in provenance performance 2.4.4 Selection of suitable provenances 2.5 Discussion 2.5.1 Absence of provenance by environment interaction 2.5.2 Ecotypic variation across species range 2.5.3 Trade-off between growth and stem form 2.5.4 Concluding remarks 2.6 Supplementary information 3 Provenances from introduced stands of Northern Red Oak (Quercus rubra L.) outperform those from the natural distribution 3.1 Abstract 3.2 Introduction 3.3 Material and methods 3.3.1 Provenances and experimental design 3.3.2 Measurements 3.3.3 Data analysis 3.4 Results 3.4.1 Percent gain in productivity 3.4.2 Provenance-environment interaction 3.4.3 Generalists vs. specialists 3.4.4 Differences in stem form 3.5 Discussion 3.5.1 Superiority of German provenances 3.5.2 Suitable P×E approaches for provenance trials 3.5.3 Use of P×E to improve provenance recommendations 3.6 Conclusion 3.7 Supplementary information 4 The IUFRO Norway spruce provenance test from 1964/68: a first conclusive evaluation of the German trial sites based on provenance groups 4.1 Abstract 4.2 Zusammenfassung 4.3 Einleitung 4.4 Material und Methoden 4.5 Ergebnisse 4.6 Diskussion 4.7 Schlussfolgerung und Ausblick 5 High phenotypic plasticity, but low signals of local adaptation to climate in a large-scale transplant experiment of Picea abies (L.) Karst. in Europe 81 5.1 Abstract 5.2 Introduction 5.3 Material and Methods 5.3.1 Common gardens 5.3.2 National forest inventories 5.3.3 Climatic and geographic data 5.3.4 OccurrenceSDM 5.3.5 TraitSDM 5.3.6 Species range change 5.4 Results 5.4.1 Habitat projections by OccurrenceSDM 5.4.2 Growth projections by TraitSDM 5.4.3 Comparison of future species range 5.5 Discussion 5.5.1 Phenotypic plasticity largely determines height growth 5.5.2 OccurrenceSDM underestimates species range 5.5.3 Limitations of the TraitSDM 5.5.4 Implications for forest management 5.6 Supplementary information 6 General discussion and synthesis 6.1 Geographic variation within species 6.2 Plasticity as a main driver of juvenile growth 6.3 Absence vs. presence of provenance by environment interactions 6.4 Evidence-based seed transfer 6.5 Implications for assisted migration 6.6 Outlook Cumulative Bibliography

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,033

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,302
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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