Your browser doesn't support javascript.
loading
Will a large complex system be productive?
Nie, Shipeng; Zheng, Junjie; Luo, Mingyu; Loreau, Michel; Gravel, Dominique; Wang, Shaopeng.
Afiliación
  • Nie S; Institute of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China.
  • Zheng J; Institute of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China.
  • Luo M; Institute of S&T Foresight and Statistics, Chinese Academy of Science and Technology for Development, Beijing, China.
  • Loreau M; Institute of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China.
  • Gravel D; Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, CNRS and Paul Sabatier University, Moulis, France.
  • Wang S; Département de Biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Ecol Lett ; 26(8): 1325-1335, 2023 Aug.
Article en En | MEDLINE | ID: mdl-37190868
ABSTRACT
While the relationship between food web complexity and stability has been well documented, how complexity affects productivity remains elusive. In this study, we combine food web theory and a data set of 149 aquatic food webs to investigate the effect of complexity (i.e. species richness, connectance, and average interaction strength) on ecosystem productivity. We find that more complex ecosystems tend to be more productive, although different facets of complexity have contrasting effects. A higher species richness and/or average interaction strength increases productivity, whereas a higher connectance often decreases it. These patterns hold not only between realized complexity and productivity, but also characterize responses of productivity to simulated declines of complexity. Our model also predicts a negative association between productivity and stability along gradients of complexity. Empirical analyses support our predictions on positive complexity-productivity relationships and negative productivity-stability relationships. Our study provides a step forward towards reconciling ecosystem complexity, productivity and stability.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ecosistema / Modelos Biológicos Tipo de estudio: Prognostic_studies Idioma: En Revista: Ecol Lett Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ecosistema / Modelos Biológicos Tipo de estudio: Prognostic_studies Idioma: En Revista: Ecol Lett Año: 2023 Tipo del documento: Article País de afiliación: China