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1 Introduction
1.1 Ecological Integrity and Self-Organization
Despite the universal uderstanding of the importance of maintaining ecological
integrity (e.g. Paris Agreement 2015; Convention on Biological Diversity Aichi
Targets 2019), a consensus on a unified theory or methodology of assessing integrity is still missing. Historically, integrity has has been understood as the degree of
“naturalsness” or the distance from a natural reference (Karr and Dudley 1981;
Majer and Beeston 1996; Scholes and Biggs 2005; Coppedge et al. 2006;
Capmourteres and Anand 2016; for a review see Ruaro and Gubiani 2013). The
approach based on naturalness estimation is known as “biotic integrity” and usually
comprises biodiversity monitoring of selected sites or specific ecosystems such as
forests, lakes or rivers (Karr and Dudley 1981; Fraser et al. 2009). Up till now, several regional scale frameworks have been proposed, adressing the multitude of ecosystem which landscapes consist of in a holistic manner, although a practical
methodology was not empirically tested so far (Slocombe 1992; Andreasen et al.
2001; Reza and Abdullah 2011).
The aim of this chapter is to describe a novel method of ecosystem integrity
evaluation in landscape context. The experimental definition of integrity used within
this study is: “Ecological integrity is the degree of self-organization. It is regulated
by different constrains imposed by abiotic factors and human management”. This
study utilizes the understanding of ecological integrity as the degree of selforganization (Müller et al. 2000; Müller 2005), or autopoiesis (Maturana and Varela
1980). Unlike the “biotic integrity” concept, the proposed approach does not quantify the distance to a natural reference, but rather the thermodynamic performance
of an ecosystem (Schneider and Kay 1994; Maes et al. 2011) or the degree of
self-organization.
Three indicators are used to estimate ecological integrity: exergy capture, biotic
water flows and abiotic heterogeneity (after Müller 2005). Based on a preceeding
literature survey, three variables were selected to represent these indicators: brightness temperature (BT), Normalized Difference Vegetation Index (NDVI) and vegetation surface heterogeneity (HG). The capacity of vegetation to reduce the
temperature gradient is a promising measure of ecosytem metabolism and integrity,
and was already proposed by Schneider and Kay (1994) and Maes et al. (2011). The
amount of temperature reduced by ecosytems is directly linked to the volume of
water transported through vegetation during evapotranspiration and can be thus
linked with the ecological integrity indicator “Biotic water flows” proposed by
Müller (2005). NDVI is a straightforward estimate of the amount of solar radiation
absorbed during photosynthesis and can be thus linked with the indicator “Exergy
capture” (Müller 2005; Kandziora et al. 2013). The third indicator, which is
ecosystem “abiotic heterogeneity”, can be estimated as the degree of ecosystem
uneveness or complexity (Müller 2005; Parrott 2010), and stands in oposition to
surface land surface homogeneity, which is typical for industrial land use.
J. Zelený and D. Mercado-Bettín
1 Introduction
1.1 Ecological Integrity and Self-Organization
Despite the universal uderstanding of the importance of maintaining ecological
integrity (e.g. Paris Agreement 2015; Convention on Biological Diversity Aichi
Targets 2019), a consensus on a unified theory or methodology of assessing integrity is still missing. Historically, integrity has has been understood as the degree of
“naturalsness” or the distance from a natural reference (Karr and Dudley 1981;
Majer and Beeston 1996; Scholes and Biggs 2005; Coppedge et al. 2006;
Capmourteres and Anand 2016; for a review see Ruaro and Gubiani 2013). The
approach based on naturalness estimation is known as “biotic integrity” and usually
comprises biodiversity monitoring of selected sites or specific ecosystems such as
forests, lakes or rivers (Karr and Dudley 1981; Fraser et al. 2009). Up till now, several regional scale frameworks have been proposed, adressing the multitude of ecosystem which landscapes consist of in a holistic manner, although a practical
methodology was not empirically tested so far (Slocombe 1992; Andreasen et al.
2001; Reza and Abdullah 2011).
The aim of this chapter is to describe a novel method of ecosystem integrity
evaluation in landscape context. The experimental definition of integrity used within
this study is: “Ecological integrity is the degree of self-organization. It is regulated
by different constrains imposed by abiotic factors and human management”. This
study utilizes the understanding of ecological integrity as the degree of selforganization (Müller et al. 2000; Müller 2005), or autopoiesis (Maturana and Varela
1980). Unlike the “biotic integrity” concept, the proposed approach does not quantify the distance to a natural reference, but rather the thermodynamic performance
of an ecosystem (Schneider and Kay 1994; Maes et al. 2011) or the degree of
self-organization.
Three indicators are used to estimate ecological integrity: exergy capture, biotic
water flows and abiotic heterogeneity (after Müller 2005). Based on a preceeding
literature survey, three variables were selected to represent these indicators: brightness temperature (BT), Normalized Difference Vegetation Index (NDVI) and vegetation surface heterogeneity (HG). The capacity of vegetation to reduce the
temperature gradient is a promising measure of ecosytem metabolism and integrity,
and was already proposed by Schneider and Kay (1994) and Maes et al. (2011). The
amount of temperature reduced by ecosytems is directly linked to the volume of
water transported through vegetation during evapotranspiration and can be thus
linked with the ecological integrity indicator “Biotic water flows” proposed by
Müller (2005). NDVI is a straightforward estimate of the amount of solar radiation
absorbed during photosynthesis and can be thus linked with the indicator “Exergy
capture” (Müller 2005; Kandziora et al. 2013). The third indicator, which is
ecosystem “abiotic heterogeneity”, can be estimated as the degree of ecosystem
uneveness or complexity (Müller 2005; Parrott 2010), and stands in oposition to
surface land surface homogeneity, which is typical for industrial land use.
J. Zelený and D. Mercado-Bettín