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Enregistrement W2009056653 · doi:10.1093/biosci/biu085

Invasive Plants May Adapt to Climate Change Better than Native Species

2014· article· en· W2009056653 sur OpenAlexaboutno aff
Laura Kiesel

Notice bibliographique

RevueBioScience · 2014
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePlant and animal studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBiologyNative plantGrowing seasonIntroduced speciesClimate changeAgronomyBotanyEcology

Résumé

récupéré en direct d'OpenAlex

Researchers have long theorized that invasive species thrive in new habitats because of the absence of natural predators. A new study suggests that rapid adaptation to changes in climate may in fact be key to invasive plants’ success—at least in the case of the purple loosestrife. The purple loosestrife (Lythrum salicaria)—an invasive wetlands plant that was introduced to North America some 50 years ago—has become the bane of conservationists who have struggled to keep it under control. The plant has crowded out cover species, such as cattails, and harmed native biodiversity in the United States and Canada. Evolutionary biologist and University of Toronto professor Spencer Barrett wanted to challenge the assumption that invasive plants thrived in their new habitats without internally changing their characteristics. To accomplish this, he and postdoctoral fellow Robert Colautti, of the University of British Columbia, planted purple loosestrife in different regions in North America to determine whether and how the plants adapted to distinct climates. Specifically, they transplanted purple loosestrife from northern Virginia to Timmins, Ontario, and vice versa in what is known as a common garden experiment. “The common garden experiment is an invaluable tool for understanding how the functioning of an organism's genes are influenced by its environment and how this… interaction ultimately affects growth, development, survival, and reproduction in nature,” says Colautti. What Barrett and Colautti found was surprising: Purple loosestrife tended to produce fewer fruits the farther away it was from its original introduction site. That was not all. Compared with the plants transplanted to Timmins from the south, the local purple loosestrife in Timmins bloomed 20 days earlier in the spring and remained small and, in doing so, maximized seed production in the shorter growing season. These local plants also yielded up to 37 times as many fruits as the southern plant grown at the same location. In contrast, the northern Ontario plants that were grown in Virginia averaged only a quarter of the seeds of the locally adapted purple loosestrife because of their earlier flowering when they were still very small. Barrett and Colautti concluded that the purple loosestrife's adaptations to different climates through changes in size and flowering times were just as important as the lack of natural pests in determining their ability to thrive. In addition, the plant was found not only to have adapted to a drastically different climate as it migrated but to have evolved this ability in a matter of mere decades. Colautti notes that the purple loosestrife found in North America contains far more genetic variability than the purple loosestrife indigenous to Europe, Asia, Africa, and parts of Australia, which suggests that there were multiple introductions of the plant from different continents to the eastern seaboard of the United States. This counters the idea of parallel introductions, which would suggest that the purple loosestrife plants that thrive in northern Canada may have been introduced from a northern climate, such as in Scandinavia, whereas those in Virginia may have been introduced from a warmer climate. Instead, the populations likely reproduced with each other, thereby maximizing their genetic variability. Barrett believes that it is the plant's identity as an outbreeder, or a plant that sexually reproduces with others in its species as opposed to cloning itself, that contributes to its resilience in new climates. “Purple loosestrife plants are adapting because they have a lot of genetic variability,” says Barrett. “More genetic variation allows for more opportunities for natural selection, which enabled the plant's northward migration.” Elizabeth Wolkovich, assistant professor in organismic and evolutionary biology at Harvard University, has conducted research comparing different temperature-dependent shifts in invasive plants. She believes that Barrett and Colautti's studies support the phenological flexibility model of plant invasions. This model suggests that species that can shift their phenologies (how they respond to cues in seasonal and climactic changes) will be very successful invaders as the climate changes. “Species that tend to be moved around a lot may increase their genetic diversity at any particular site, which could make them more locally adapted… and, therefore, better able to exploit climate change and its earlier growing season than native species,” says Wolkovich. Colautti is now working on a related line of research on invasive garlic mustard (Alliaria petiolata), in a collaborative project involving over 150 scientists from 16 countries. Said Colautti, “The purple loosestrife work was a major motivation for this project, because it crystallized in my mind how important it is to characterize variation among sites within North America and Europe before making broadscale comparisons between native and introduced regions.”

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)0,000
score de la tête « metaresearch » (Gemma)0,000
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 enseignants0,004
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,117
Tête enseignante GPT0,232
Écart entre enseignants0,115 · 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

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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