Using food-web theory to conserve ecosystems.
Nat Commun
; 7: 10245, 2016 Jan 18.
Article
en En
| MEDLINE
| ID: mdl-26776253
Food-web theory can be a powerful guide to the management of complex ecosystems. However, we show that indices of species importance common in food-web and network theory can be a poor guide to ecosystem management, resulting in significantly more extinctions than necessary. We use Bayesian Networks and Constrained Combinatorial Optimization to find optimal management strategies for a wide range of real and hypothetical food webs. This Artificial Intelligence approach provides the ability to test the performance of any index for prioritizing species management in a network. While no single network theory index provides an appropriate guide to management for all food webs, a modified version of the Google PageRank algorithm reliably minimizes the chance and severity of negative outcomes. Our analysis shows that by prioritizing ecosystem management based on the network-wide impact of species protection rather than species loss, we can substantially improve conservation outcomes.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Ecosistema
/
Cadena Alimentaria
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Nat Commun
Asunto de la revista:
BIOLOGIA
/
CIENCIA
Año:
2016
Tipo del documento:
Article
País de afiliación:
Australia