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The significance of pastures

estimates. Tubiello et al (2007) summarizes the responses to climate change
as follows: (1) nonlinearity and threshold effects as a response to the frequency
of extreme conditions; (2) altered incidence of pests, diseases, and weeds; (3)
the farm response to the high CO2 in crops (4) the interaction of climate and
management variables due to elevated CO2. To reduce the uncertainties in
the predictions on climate change effects, and assess future risks accurately,
research on responses of product and pasture types should continue. Wrong
food and livestock breeding management affects global carbon pool to
a great extent and may the result in a security gap in atmospheric CO2
concentrations (Ciais et al, 2005; Cox et al, 2004; Tubiello et al, 2007).
The decrease in the vulnerability of carbon sinks to climate change is essential
for the sustainability of pastures. Potential changes in carbon cycles depend
largely on land management practices such as land use planning (pasture
improvement, forestation, etc.), the use of nitrogen fertilizers, irrigation and
cultivation. In the last 15 years, a great deal of experiential data has been
produced. However, this data could not reach the farmers’ land and could not
be internalized on a regional scale, failing even in the estimates of CO2 levels.
For models towards responses to CO2 based on land, there is need for further
collaboration and a bridge between interdisciplinary researchers is necessary
for compensating for the lack of current data (Tubiello et al, 2007).

Method and Findings

The current study investigates the main ongoing conflicts over the pastures
in Türkiye through literature review and media analysis. This was followed by
the field studies, on-site observations, semi-structured interviews with local
administrators and experts (including members of the Provincial Pasture
Commissions, Chambers of Agriculture, Ege University, Faculty of Agriculture,
etc.) And finally, the data gained from all these activities and the “Group
Consensus Workshop” (2018) held in Ege University was evaluated through
content analysis, a pasture indications set was created.
The pasture indicators were adapted to the DPSIR causal analysis model
used in the Environmental Performance Reports (EPR) by the European
Environment Agency (EEA). DPSIR causal analysis model provides quick
feedbacks in decision-making processes and thus facilitates communication
(EEA, 1999). At the end of the process, through this model, responses (-R)
were generated to drivers, pressures, states and impacts (DPSI-) identified in
pastures (Hazar and Velibeyoğlu, 2019).

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