TY - JOUR

T1 - Performance of methods to select landscape metrics for modelling species richness

AU - Schindler, Stefan

AU - von Wehrden, Henrik

AU - Poirazidis, Kostas

AU - Hochachka, Wesley M.

AU - Wrbka, Thomas

AU - Kati, Vassiliki

PY - 2015/1/10

Y1 - 2015/1/10

N2 - Landscape metrics are commonly used indicators of ecological pattern and processes in ecological modelling. Numerous landscape metrics are available, making the selection of appropriate metrics a common challenge in model development. In this paper, we tested the performance of methods for preselecting sets of three landscape metrics for use in modelling species richness of six groups of organisms (woody plants, orchids, orthopterans, amphibians, reptiles, and small terrestrial birds) and overall species richness in a Mediterranean forest landscape. The tested methods included expert knowledge, decision tree analysis, principal component analysis, and principal component regression. They were compared with random choice and optimal sets, which were evaluated by testing all possible combinations of metrics. All pre-selection methods performed significantly worse than the optimal sets. The statistical approaches performed slightly better than random choice that in turn performed slightly better than sets derived by expert knowledge. We concluded that the process of selecting the most appropriate landscape metrics for modelling biodiversity is not trivial and that shortcuts to systematic evaluation of metrics should not be expected to identify appropriate indicators.

AB - Landscape metrics are commonly used indicators of ecological pattern and processes in ecological modelling. Numerous landscape metrics are available, making the selection of appropriate metrics a common challenge in model development. In this paper, we tested the performance of methods for preselecting sets of three landscape metrics for use in modelling species richness of six groups of organisms (woody plants, orchids, orthopterans, amphibians, reptiles, and small terrestrial birds) and overall species richness in a Mediterranean forest landscape. The tested methods included expert knowledge, decision tree analysis, principal component analysis, and principal component regression. They were compared with random choice and optimal sets, which were evaluated by testing all possible combinations of metrics. All pre-selection methods performed significantly worse than the optimal sets. The statistical approaches performed slightly better than random choice that in turn performed slightly better than sets derived by expert knowledge. We concluded that the process of selecting the most appropriate landscape metrics for modelling biodiversity is not trivial and that shortcuts to systematic evaluation of metrics should not be expected to identify appropriate indicators.

KW - Ecosystems Research

KW - Biodiversity indicator

KW - Dadia National Park

KW - Ecological indicator

KW - Greece

KW - Landscape structure

KW - Variable selection

KW - variable selection

KW - biodiversity indicator

KW - ecological indicator

KW - landscape structure

KW - Dadia National Park

KW - Greece

UR - http://www.scopus.com/inward/record.url?scp=84910075581&partnerID=8YFLogxK

U2 - 10.1016/j.ecolmodel.2014.05.012

DO - 10.1016/j.ecolmodel.2014.05.012

M3 - Journal articles

VL - 295

SP - 107

EP - 112

JO - Ecological Modelling

JF - Ecological Modelling

SN - 0304-3800

ER -