Pattern formation - A missing link in the study of ecosystem response to environmental changes

نتاج البحث: نشر في مجلةمقالةمراجعة النظراء


Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions.

اللغة الأصليةإنجليزيّة أمريكيّة
الصفحات (من إلى)1-18
عدد الصفحات18
دوريةMathematical Biosciences
مستوى الصوت271
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 1 يناير 2016

All Science Journal Classification (ASJC) codes

  • !!General Immunology and Microbiology
  • !!Applied Mathematics
  • !!General Biochemistry, Genetics and Molecular Biology
  • !!General Agricultural and Biological Sciences
  • !!Statistics and Probability
  • !!Modeling and Simulation


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