 |
| Titel |
A fuzzy multi-objective linear programming approach for integrated sheep farming and wildlife in land management decisions: a case study in the Patagonian rangelands |
| VerfasserIn |
Graciela Metternicht, Paula Blanco, Hector del Valle, Pedro Laterra, Leonardo Hardtke, Pablo Bouza |
| Konferenz |
EGU General Assembly 2015
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250108489
|
| Publikation (Nr.) |
 EGU/EGU2015-8244.pdf |
|
|
|
|
|
| Zusammenfassung |
| Wildlife is part of the Patagonian rangelands sheep farming environment, with the
potential of providing extra revenue to livestock owners. As sheep farming became less
profitable, farmers and ranchers could focus on sustainable wildlife harvesting. It has
been argued that sustainable wildlife harvesting is ecologically one of the most
rational forms of land use because of its potential to provide multiple products of
high value, while reducing pressure on ecosystems. The guanaco (Lama guanicoe)
is the most conspicuous wild ungulate of Patagonia. Guanaco ?bre, meat, pelts
and hides are economically valuable and have the potential to be used within the
present Patagonian context of production systems. Guanaco populations in South
America, including Patagonia, have experienced a sustained decline. Causes for
this decline are related to habitat alteration, competition for forage with sheep,
and lack of reasonable management plans to develop livelihoods for ranchers. In
this study we propose an approach to explicitly determinate optimal stocking rates
based on trade-offs between guanaco density and livestock grazing intensity on
rangelands.
The focus of our research is on finding optimal sheep stocking rates at paddock
level, to ensure the highest production outputs while: a) meeting requirements of
sustainable conservation of guanacos over their minimum viable population; b)
maximizing soil carbon sequestration, and c) minimizing soil erosion. In this way,
determination of optimal stocking rate in rangelands becomes a multi-objective optimization
problem that can be addressed using a Fuzzy Multi-Objective Linear Programming
(MOLP) approach. Basically, this approach converts multi-objective problems into
single-objective optimizations, by introducing a set of objective weights. Objectives are
represented using fuzzy set theory and fuzzy memberships, enabling each objective
function to adopt a value between 0 and 1. Each objective function indicates the
satisfaction of the decision maker towards the respective objective. Fuzzy logic
is closer to intuitive thinking used by decision makers, making it a user-friendly
approach for them to select alternatives. The proposed approach was applied in a
study area of approximately 40,000 hectares in semiarid Patagonian rangelands
where extensive, continuous sheep grazing for wool production is the main land
use.
Multi- and hyper-spectral data were combined with ancillary data within a GIS
environment, and used to derive maps of forage production, guanacos density, soil organic
carbon and soil erosion. Different scenarios, with different objectives weights were evaluated.
Results showed that under scenario 1, where livestock production is predicted to have
the highest values, guanaco numbers decrease substantially as well as soil carbon
sequestration, and soil erosion exhibit the highest values. On the other hand, when guanaco
population is prioritized, livestock production has the lowest value. A compromise
alternative resulted from a scenario where variables are assigned same weight; under this
condition, high livestock production is predicted, while conservation of guanaco
population is sustainable, carbon sequestration is maximized and soil erosion minimized. |
|
|
|
|
|
|