Performance trade-off across a natural resource gradient

Oecologia ◽  
1999 ◽  
Vol 120 (1) ◽  
pp. 137-146 ◽  
Author(s):  
Kristen H. Desmarais ◽  
Alan J. Tessier
2010 ◽  
Vol 16 (1) ◽  
pp. 15-36 ◽  
Author(s):  
Armando A. Rodriguez ◽  
Oguzhan Cifdaloz ◽  
John Martin Anderies ◽  
Marco A. Janssen ◽  
Jeffrey Dickeson

2019 ◽  
Vol 21 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Daniel K. Okamoto ◽  
Melissa R. Poe ◽  
Tessa B. Francis ◽  
André E. Punt ◽  
Phillip S. Levin ◽  
...  

Oikos ◽  
2020 ◽  
Vol 130 (1) ◽  
pp. 66-78
Author(s):  
Udi Segev ◽  
Katja Tielbörger ◽  
Yael Lubin ◽  
Jaime Kigel

2009 ◽  
Vol 49 (10) ◽  
pp. 826 ◽  
Author(s):  
Michael Robertson ◽  
Andrew Bathgate ◽  
Andrew Moore ◽  
Roger Lawes ◽  
Julianne Lilley

Natural resource indicators are used by catchment management organisations as targets for land use management. However, the nature of the trade-off function between natural resource management (NRM) outcomes and whole-farm profit is ill-defined, and varies between regions and according to the particular NRM indicator considered. Defining this function will assist catchment management organisations and farmers to evaluate the achievability of particular targets, and help determine the size of economic incentives required to offset any expected loss in farm profit associated with meeting targets. We addressed this issue by modelling representative farm businesses in two mixed farming regions (southern New South Wales and the central wheatbelt of Western Australia). The Agricultural Production Systems Simulator (APSIM) and GRAZPLAN farming systems models were linked and used to generate values of four NRM indicators (water leakage, nitrate leaching, groundcover and soil organic carbon change) for a wide range of crop–pasture rotations. The NRM indicator values were then incorporated into the Model of an Integrated Dryland System (MIDAS) whole-farm economic model to define the relationship with farm profit and farm cropping percentage. For some circumstances and indicators, the resulting trade-off functions were relatively flat; a wide range of enterprise mixes can lead to the same NRM outcomes but significant gains in the indicators may not be possible using current rotation options. For others, significant improvements could be achieved but at a substantial loss in whole-farm profit (through the selection of less profitable rotations). There were also examples where simultaneous gains in indicators and farm profit were possible. This analysis demonstrates an approach by which biophysical simulation models of the farming system can be linked to linear-programming representations of farming enterprises, and provides a method for deriving relationships between NRM targets and economic performance.


1982 ◽  
Vol 14 (2) ◽  
pp. 109-113 ◽  
Author(s):  
Suleyman Tufekci
Keyword(s):  

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