Document
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Consejo Nacional de Ciencia y Tecnologia de Mexico [FORDECYT 297525]; GIZ
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type: BFO_0000020
type: Entity
type: Thing
type: Grant
type: Continuant
funding vehicle for: Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation

Continuant
type: Class

Entity
type: Class

Generically Dependent Continuant
type: Class

individual
rights: termsOfUse
date: 2026-08-25T22:12:00
publisher: vivo
type: Document
label: RDF description of Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation - http://orbis.uaslp.mx/vivo/individual/d11544

Article
type: Class

Journal of Environmental Management
type: Periodical
type: Thing
type: Generically Dependent Continuant
type: Entity
type: Information Content Entity
type: Continuant
publication venue for: Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation
type: Document
type: Collection
type: Journal

Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation
type: Continuant
abstract: The long-term success of forest restoration programs can be improved using climate-based species distribution models (SDMs) to predict which tree species will tolerate climate change. However, as SDMs cannot estimate if species will recruit at these habitats, determining whether their predictions apply to early life-cycle stages of trees is critical to support such a usage. For this, we propose sowing seeds of the focal tree species under the current climate and simulated climate change conditions in target restoration sites. Thus, using of SDMs to design climate-adaptive forest restoration programs would be supported if the differences in habitat occupancy probabilities of species they predict between the current and future climate concurs with the observed differences in recruitment rates of species when sowed under the current climate and simulated climate change conditions. To test this hypothesis, we calibrated SDMs for Vachellia pennatula and Prosopis laevigata, two pioneer tree species widely recommended to restore human-degraded drylands in Mexico, and transferred them to climate change scenarios. After that, we applied the experimental approach proposed above to validate the predictions of SDMs. These models predicted that V. pennatula will decrease its habitat occupancy probabilities across Mexico, while P. laevigata was predicted to keep out their current habitat occupancy probabilities, or even increase them, in climate change scenarios. The results of the field experiment supported these predictions, as recruitment rates of V. pennatula were lower under simulated climate change than under the current climate, while no differences were found for the recruitment rates of P. laevigata between these environmental conditions. These findings demonstrate that SDMs provide meaningful insights for designing climate-adaptive forest restoration programs but, before applying this methodology, predictions of these models must be validated with field experiments to d…
pmid: 36528941
most specific type: Article
date time value: article date 11545
artnum: 117038
type: Document
related by: authorship_73420
type: Article
related by: authorship_73419
type: Information Content Entity
volume: 329
doi: 10.1016/j.jenvman.2022.117038
type: Generically Dependent Continuant
type: Entity
has publication venue: Journal of Environmental Management
estado: published
type: Thing
crisid: 11545
most specific type: Document
freetext keyword: Climate change experiments; Warming effects; Drought effects; Ecological restoration; MaxEnt
has funding vehicle: Consejo Nacional de Ciencia y Tecnologia de Mexico [FORDECYT 297525]; GIZ

Information Content Entity
type: Class