Panarchy rules? : rethinking resilience of agroecosystems

Research output: Thesisinternal PhD, WU

Abstract

This thesis explores the applicability of the resilience perspective on agro-ecosystems dynamics. It start out by using the five heuristics of the resilience perspective on intensive agricultural systems. Simulations with a dynamic farm model suggest that conventional farming short cuts the adaptive cycle leading to an ‘incremental adaptation’ trap. Panarchy is therefore claimed as a leading heuristic to understand long-term dynamics and current management characteristics. This interaction of long-term dynamics with current management leads to an asymmetry in the landscape. This asymmetry leads to windows of opportunities for farmers. However, disregarding the cross-scale nature of the asymmetry might also lead to a cascade of events that undermine the resilience of the landscape as whole. The cross-scale interactions of landscape dynamics and farm management suggest a co-evolution of production intensity and landscape pattern. Moreover trajectories of intensification might even be linked to certain tipping points of combinations of landscape characteristics and management. Therefore the landscape asymmetry might yield insight in agro-ecosystem functioning. The landscape asymmetry potentially provides a level of self-organisation above the farm. However, identifying the asymmetry appeared to be problematic. Next to scale issues, the current pattern does not necessary result from current management, leading to a de-coupling of pattern and process. A re-coupling of management and landscape asymmetry can exploit positive feedbacks. I suggest the use of identity to locate asymmetries and to use space-time substitutions to experiment with the typical slow variables that shape the asymmetry.

The theory developed in this thesis is grounded on empirical farm management data and dynamical model simulation of intensive dairy farming in the Netherlands and small-holder systems in Zimbabwe.

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Giller, Ken, Promotor
  • Kok, Kasper, Co-promotor
  • Sonneveld, Marthijn, Co-promotor
Award date22 Apr 2014
Place of PublicationWageningen
Publisher
Print ISBNs9789461739179
Publication statusPublished - 2014

Fingerprint

agricultural ecosystem
asymmetry
farm
heuristics
dairy farming
space use
self organization
ecosystem dynamics
data management
smallholder
coevolution
farming system
simulation
substitution
trajectory
ecosystem

Keywords

  • agroecosystems
  • sustainability
  • farming systems
  • soil organic matter
  • mathematical models
  • systems analysis
  • netherlands
  • zimbabwe

Cite this

van Apeldoorn, D.F.. / Panarchy rules? : rethinking resilience of agroecosystems. Wageningen : Wageningen University, 2014. 137 p.
@phdthesis{dec2b0c1f36347e7b155f9d926772c6e,
title = "Panarchy rules? : rethinking resilience of agroecosystems",
abstract = "This thesis explores the applicability of the resilience perspective on agro-ecosystems dynamics. It start out by using the five heuristics of the resilience perspective on intensive agricultural systems. Simulations with a dynamic farm model suggest that conventional farming short cuts the adaptive cycle leading to an ‘incremental adaptation’ trap. Panarchy is therefore claimed as a leading heuristic to understand long-term dynamics and current management characteristics. This interaction of long-term dynamics with current management leads to an asymmetry in the landscape. This asymmetry leads to windows of opportunities for farmers. However, disregarding the cross-scale nature of the asymmetry might also lead to a cascade of events that undermine the resilience of the landscape as whole. The cross-scale interactions of landscape dynamics and farm management suggest a co-evolution of production intensity and landscape pattern. Moreover trajectories of intensification might even be linked to certain tipping points of combinations of landscape characteristics and management. Therefore the landscape asymmetry might yield insight in agro-ecosystem functioning. The landscape asymmetry potentially provides a level of self-organisation above the farm. However, identifying the asymmetry appeared to be problematic. Next to scale issues, the current pattern does not necessary result from current management, leading to a de-coupling of pattern and process. A re-coupling of management and landscape asymmetry can exploit positive feedbacks. I suggest the use of identity to locate asymmetries and to use space-time substitutions to experiment with the typical slow variables that shape the asymmetry. The theory developed in this thesis is grounded on empirical farm management data and dynamical model simulation of intensive dairy farming in the Netherlands and small-holder systems in Zimbabwe.",
keywords = "agro-ecosystemen, duurzaamheid (sustainability), bedrijfssystemen, organisch bodemmateriaal, wiskundige modellen, systeemanalyse, nederland, zimbabwe, agroecosystems, sustainability, farming systems, soil organic matter, mathematical models, systems analysis, netherlands, zimbabwe",
author = "{van Apeldoorn}, D.F.",
note = "WU thesis 5719",
year = "2014",
language = "English",
isbn = "9789461739179",
publisher = "Wageningen University",
school = "Wageningen University",

}

van Apeldoorn, DF 2014, 'Panarchy rules? : rethinking resilience of agroecosystems', Doctor of Philosophy, Wageningen University, Wageningen.

Panarchy rules? : rethinking resilience of agroecosystems. / van Apeldoorn, D.F.

Wageningen : Wageningen University, 2014. 137 p.

Research output: Thesisinternal PhD, WU

TY - THES

T1 - Panarchy rules? : rethinking resilience of agroecosystems

AU - van Apeldoorn, D.F.

N1 - WU thesis 5719

PY - 2014

Y1 - 2014

N2 - This thesis explores the applicability of the resilience perspective on agro-ecosystems dynamics. It start out by using the five heuristics of the resilience perspective on intensive agricultural systems. Simulations with a dynamic farm model suggest that conventional farming short cuts the adaptive cycle leading to an ‘incremental adaptation’ trap. Panarchy is therefore claimed as a leading heuristic to understand long-term dynamics and current management characteristics. This interaction of long-term dynamics with current management leads to an asymmetry in the landscape. This asymmetry leads to windows of opportunities for farmers. However, disregarding the cross-scale nature of the asymmetry might also lead to a cascade of events that undermine the resilience of the landscape as whole. The cross-scale interactions of landscape dynamics and farm management suggest a co-evolution of production intensity and landscape pattern. Moreover trajectories of intensification might even be linked to certain tipping points of combinations of landscape characteristics and management. Therefore the landscape asymmetry might yield insight in agro-ecosystem functioning. The landscape asymmetry potentially provides a level of self-organisation above the farm. However, identifying the asymmetry appeared to be problematic. Next to scale issues, the current pattern does not necessary result from current management, leading to a de-coupling of pattern and process. A re-coupling of management and landscape asymmetry can exploit positive feedbacks. I suggest the use of identity to locate asymmetries and to use space-time substitutions to experiment with the typical slow variables that shape the asymmetry. The theory developed in this thesis is grounded on empirical farm management data and dynamical model simulation of intensive dairy farming in the Netherlands and small-holder systems in Zimbabwe.

AB - This thesis explores the applicability of the resilience perspective on agro-ecosystems dynamics. It start out by using the five heuristics of the resilience perspective on intensive agricultural systems. Simulations with a dynamic farm model suggest that conventional farming short cuts the adaptive cycle leading to an ‘incremental adaptation’ trap. Panarchy is therefore claimed as a leading heuristic to understand long-term dynamics and current management characteristics. This interaction of long-term dynamics with current management leads to an asymmetry in the landscape. This asymmetry leads to windows of opportunities for farmers. However, disregarding the cross-scale nature of the asymmetry might also lead to a cascade of events that undermine the resilience of the landscape as whole. The cross-scale interactions of landscape dynamics and farm management suggest a co-evolution of production intensity and landscape pattern. Moreover trajectories of intensification might even be linked to certain tipping points of combinations of landscape characteristics and management. Therefore the landscape asymmetry might yield insight in agro-ecosystem functioning. The landscape asymmetry potentially provides a level of self-organisation above the farm. However, identifying the asymmetry appeared to be problematic. Next to scale issues, the current pattern does not necessary result from current management, leading to a de-coupling of pattern and process. A re-coupling of management and landscape asymmetry can exploit positive feedbacks. I suggest the use of identity to locate asymmetries and to use space-time substitutions to experiment with the typical slow variables that shape the asymmetry. The theory developed in this thesis is grounded on empirical farm management data and dynamical model simulation of intensive dairy farming in the Netherlands and small-holder systems in Zimbabwe.

KW - agro-ecosystemen

KW - duurzaamheid (sustainability)

KW - bedrijfssystemen

KW - organisch bodemmateriaal

KW - wiskundige modellen

KW - systeemanalyse

KW - nederland

KW - zimbabwe

KW - agroecosystems

KW - sustainability

KW - farming systems

KW - soil organic matter

KW - mathematical models

KW - systems analysis

KW - netherlands

KW - zimbabwe

M3 - internal PhD, WU

SN - 9789461739179

PB - Wageningen University

CY - Wageningen

ER -

van Apeldoorn DF. Panarchy rules? : rethinking resilience of agroecosystems. Wageningen: Wageningen University, 2014. 137 p.