As the goals of this dissertation are to examine the influence of the various GNP stakeholders and post-Soviet land reform processes on the Park’s landscape changes relevant to Park conservation and the Park’s management goals, three basic research goals are
addressed:
1) Understand the interests of GNP stakeholder groups and analyze how landuse policy changes in GNP are shaped by these stakeholder groups’ interests and values (Chapter 2);
2) Understand how the post-Soviet changes in composition and pattern of the GNP landscape have affected key Park resources of stakeholder interest – these resources, identified in Chapter 2, are biodiversity and the natural and cultural landscapes (Chapter 3);
3) Determine the important drivers of landuse/landcover change in GNP, examine how they have changed over time, and assess how these factors are associated with landowner opinions regarding management of the Park (Chapter 4).
Methods
This landuse/landcover change research integrates quantitative GIS, remote sensing, and statistical analyses with a qualitative assessment of GNP stakeholder values, interests, and conflicts. This integration of multiple research methods provides for a broader
perspective of the drivers and consequences of landuse and landcover change than either method would provide in isolation. Detailed discussions of methods for each research objective are given in their respective chapters. A brief overview of the methods for the entire project is outlined here.
Most actions of the multiple stakeholder groups in GNP, and their influences on LU/LC change in the Park, cannot be wholly understood in isolation. The
interconnectedness among stakeholder groups, the transformations in some of these groups, and the conflicts between them must be understood to comprehend their direct and indirect effects on changes in GNP’s LU/LC. To provide the local contextual framework and to understand the interactions of these important factors, a qualitative study was undertaken in GNP, which helped direct the quantitative LU/LC change research. To identify GNP
stakeholders and assess their values, interests, and conflicts, open-ended interviews were conducted with key informants. These interviews were directed to understand the policies and processes affecting landuse change in the Park, to understand the stakeholder groups’ interests regarding landuse in the Park, and to understand important interactions between the stakeholder groups. A detailed discussion of the methods for this portion of the research is presented with the rest of this research in Chapter 2.
Chapter 3 evaluates how the post-Soviet changes in composition and pattern of the GNP landscape have affected biodiversity and the natural and cultural landscapes. The primary data used for these analyses were a time series of Landsat Thematic Mapper (TM) images with a temporal coverage from the late Soviet era through today. The obtained images, with dates from leaf-on periods of the summers of 1985, 1994, 1999, and 2002, were preprocessed and classified in preparation for landcover change analyses. Landsat TM was chosen due to its sufficient temporal coverage, and its spatial and spectral resolution, designed for determining general landcover at the landscape scale. Ground control data for purposes of image georectification and to aid in classification labeling were obtained via in- situ field work in the Park utilizing Global Positioning Systems (GPS) data. The changes in landscape composition and patterns (through the computation of ecological pattern metrics) were analyzed over time with respect to landscape characteristics associated with
biodiversity and the cultural and natural landscapes of the Park. These changes are discussed in relation to the landscape processes and stakeholder interests and conflicts identified in Chapter 2.
In Chapter 4, research was conducted to identify influential drivers of LU/LC change in GNP, understand the effects of these drivers on landcover change, and determine how the
influence of certain drivers changed over time. Classification tree analyses and multinomial logistic regression models were developed for each pair of consecutive Landsat TM image dates, and for the 1985 – 2002 image pair (that represents the first and last images in the time-series). The dependent variable in these models was landcover change, and the independent variables represented geographic, biophysical, and political forces and factors, spatially represented in the landscape. The statistical models were used to assess the effects of these independent variables on landcover change. The spatially referenced independent variables and the Landsat TM images were integrated through the use of Geographic Information Systems (GIS). The statistical analyses were conducted at the pixel level.
Finally, responses to a GNP landowner survey conducted by the Gauja National Park Administration (GNP Management 1999) were geocoded in 2004 through address matching between the original survey responses and a GIS data layer of addresses for each building in GNP, assembled by the GNP Administration. Bivariate associations were analyzed in Chapter 4 between each of the geographically referenced drivers of landcover change (as determined by the statistical models) and the opinions of GNP landowners (whose homes were geocoded from the landowner survey) towards the Park’s protection and development policies. Only bivariate statistical analyses were performed because of the small sample size of valid, geocoded landowner survey responses.