Developing an ecology of respect: Shared land use by humans and wolves through “ecological labour” in Lusatia

Jordan Oelke

doi:10.14512/rur.3059

Authors

Jordan Oelke

DOI:

https://doi.org/10.14512/rur.3059

Keywords:

Ecological labour, Human-wildlife conflict, Structural transformation, Lusatia

Abstract

Present land-use forms, such as former coal mines turned into lakes, solar parks, wind farms, mixed/test forests and biological (organic) agriculture, cater more for ‘human wellbeing’ or building sustainable economies than to the overall ecological well-being of landscapes that include animals and other species. A more ecologically oriented form of labour based in eco-Marxism is utilised throughout this paper, tying together various human and non-human actors. This approach is an analytical tool revealing the benefits of both wolves and humans for the landscape in order to move beyond a hegemonic economic-oriented model. Such a model, historically, viewed the overlapping territories of humans and wolves as an issue that needed to be dealt with, resulting in the near extermination of wolves in Germany. It now allows the wolves to exist in the landscape as a test model for biodiversity in the cultural landscape. This experiment has affected certain actors more negatively than others and requires an honest review and consolidation. In their attempts to provide alternatives to this land-use planning model, human actors, such as sheep farmers and hunters, view their work with the animals they exert sovereignty over in ecological terms, regarding the land as part of their territory that must be cared for and sustained. Meanwhile, wolves provide valuable ecological services to the landscape that at times are feared rather than valued. Deconstructing the perceived threat of the Wolf as both a material and symbolic threat and learning to respect the presence and contribution of wolves to the landscape helps build inclusive land-use forms for co-habitation in working towards a ‘sustainable’ and ‘just’ landscape for all.

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