Multi-scale spatial ecology analyses: a Kullback information approach
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Multi-scale spatial ecology analyses : a Kullback information approach. / Huckeba, Gintare; Andresen, Bjarne; Roach, Ty N. F.
I: Landscape Ecology, Bind 38, 01.05.2023, s. 645-657.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Multi-scale spatial ecology analyses
T2 - a Kullback information approach
AU - Huckeba, Gintare
AU - Andresen, Bjarne
AU - Roach, Ty N. F.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Context The way organisms are patterned in space dictates the outcome of many ecological processes such as growth, survival, colonization, and migration. The field of landscape ecology has developed quantitative metrics to describe spatial patterning using the concept of entropy. However, a general theory of how these patterns relate to one another within and between different organizational levels and over different spatial scales has remained incomplete. Objectives Review how statistical versions of entropy have been applied to detect spatial organization and propose a theoretical framework to use Kullback-Leibler relative entropy for cross-scale analyses on a landscape of any size. Methods Examine previous efforts using entropy in landscape ecology and introduce a Kullback Information Index as a next step in the science of scaling. Results Entropic indices can provide compositional and configurational information about a system and can be used to detect landscape patterns. Yet, most entropy-based metrics are scale-dependent, highlighting the need to find a common currency for comparative analysis across scales. The non-symmetric unitless property of the Kullback-Leibler relative entropy may remedy that since it is theoretically capable of comparing variables and scales. The proposed framework can be extended to describe any system that contains scalable modules of interest, which will advance scaling in landscape ecology and other disciplines. Conclusions The Kullback Information Index describes landscapes' compositional and configurational patterns across scales. Since relative entropy is connected to information theory and thermodynamics, the framework's results can be interpreted within a broader ecological context.
AB - Context The way organisms are patterned in space dictates the outcome of many ecological processes such as growth, survival, colonization, and migration. The field of landscape ecology has developed quantitative metrics to describe spatial patterning using the concept of entropy. However, a general theory of how these patterns relate to one another within and between different organizational levels and over different spatial scales has remained incomplete. Objectives Review how statistical versions of entropy have been applied to detect spatial organization and propose a theoretical framework to use Kullback-Leibler relative entropy for cross-scale analyses on a landscape of any size. Methods Examine previous efforts using entropy in landscape ecology and introduce a Kullback Information Index as a next step in the science of scaling. Results Entropic indices can provide compositional and configurational information about a system and can be used to detect landscape patterns. Yet, most entropy-based metrics are scale-dependent, highlighting the need to find a common currency for comparative analysis across scales. The non-symmetric unitless property of the Kullback-Leibler relative entropy may remedy that since it is theoretically capable of comparing variables and scales. The proposed framework can be extended to describe any system that contains scalable modules of interest, which will advance scaling in landscape ecology and other disciplines. Conclusions The Kullback Information Index describes landscapes' compositional and configurational patterns across scales. Since relative entropy is connected to information theory and thermodynamics, the framework's results can be interpreted within a broader ecological context.
KW - Spatial organization
KW - Landscape patterns
KW - Diversity
KW - Information theory
KW - Thermodynamics
KW - Entropy
KW - LANDSCAPE ECOLOGY
KW - ENTROPY
KW - PATTERNS
KW - TIME
U2 - 10.1007/s10980-022-01514-9
DO - 10.1007/s10980-022-01514-9
M3 - Journal article
VL - 38
SP - 645
EP - 657
JO - Landscape Ecology
JF - Landscape Ecology
SN - 0921-2973
ER -
ID: 319779996