Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

Proximal microclimate: Moving beyond spatiotemporal resolution improves ecological predictions

Klinges, David H.; Baecher, J. Alex; Lembrechts, Jonas J.; Maclean, Ilya M. D.; Lenoir, Jonathan; Greiser, Caroline; Ashcroft, Michael; Evans, Luke J.; Kearney, Michael R.; Aalto, Juha; Barrio, Isabel C.; De Frenne, Pieter; Guillemot, Joannès; Hylander, Kristoffer; Jucker, Tommaso; Kopecký, Martin; Luoto, Miska; Macek, Martin; Nijs, Ivan; Urban, Josef; Brink, Liesbeth van den; Vangansbeke, Pieter; Oppen, Jonathan Von; Wild, Jan; Boike, Julia; Canessa, Rafaella; Nosetto, Marcelo DanielIcon ; Rubtsov, Alexey; Sallo Bravo, Jhonatan; Scheffers, Brett R.
Fecha de publicación: 06/2024
Editorial: Wiley Blackwell Publishing, Inc
Revista: Global Ecology and Biogeography
ISSN: 1466-822X
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias Naturales y Exactas

Resumen

Aim The scale of environmental data is often defined by their extent (spatial area, temporal duration) and resolution (grain size, temporal interval). Although describing climate data scale via these terms is appropriate for most meteorological applications, for ecology and biogeography, climate data of the same spatiotemporal resolution and extent may differ in their relevance to an organism. Here, we propose that climate proximity, or how well climate data represent the actual conditions that an organism is exposed to, is more important for ecological realism than the spatiotemporal resolution of the climate data. Location Temperature comparison in nine countries across four continents; ecological case studies in Alberta (Canada), Sabah (Malaysia) and North Carolina/Tennessee (USA). Time Period 1960–2018. Major Taxa Studied Case studies with flies, mosquitoes and salamanders, but concepts relevant to all life on earth. Methods We compare the accuracy of two macroclimate data sources (ERA5 and WorldClim) and a novel microclimate model (microclimf) in predicting soil temperatures. We then use ERA5, WorldClim and microclimf to drive ecological models in three case studies: temporal (fly phenology), spatial (mosquito thermal suitability) and spatiotemporal (salamander range shifts) ecological responses. Results For predicting soil temperatures, microclimf had 24.9% and 16.4% lower absolute bias than ERA5 and WorldClim respectively. Across the case studies, we find that increasing proximity (from macroclimate to microclimate) yields a 247% improvement in performance of ecological models on average, compared to 18% and 9% improvements from increasing spatial resolution 20-fold, and temporal resolution 30-fold respectively. Main Conclusions We propose that increasing climate proximity, even if at the sacrifice of finer climate spatiotemporal resolution, may improve ecological predictions. We emphasize biophysically informed approaches, rather than generic formulations, when quantifying ecoclimatic relationships. Redefining the scale of climate through the lens of the organism itself helps reveal mechanisms underlying how climate shapes ecological systems.
Palabras clave: BIOPHYSICAL ECOLOGY , CLIMATE CHANGE , ECOPHYSIOLOGY , MACROCLIMATE , MICROCLIMATE , NONLINEARITY , RESOLUTION , SPECIES DISTRIBUTION MODEL
Ver el registro completo
 
Archivos asociados
Tamaño: 5.492Mb
Formato: PDF
.
Solicitar
Licencia
info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/247484
URL: https://onlinelibrary.wiley.com/doi/10.1111/geb.13884
DOI: http://dx.doi.org/10.1111/geb.13884
Colecciones
Articulos(IMASL)
Articulos de INST. DE MATEMATICA APLICADA DE SAN LUIS
Citación
Klinges, David H.; Baecher, J. Alex; Lembrechts, Jonas J.; Maclean, Ilya M. D.; Lenoir, Jonathan; et al.; Proximal microclimate: Moving beyond spatiotemporal resolution improves ecological predictions; Wiley Blackwell Publishing, Inc; Global Ecology and Biogeography; 33; 9; 6-2024; 1-16
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES