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Amano, & Katoh, 2008), we tried to fill this gap in this case study.
5
We anal-
ysed the relations of 52 landscape structure variables with overall biodiversity
and with species richness of the six taxa woody plants, orchids, orthopterans,
amphibians, reptiles and birds. Species data were collected by Kati et al. (2004a),
based on standard methods; landscape structure variables were computed for circu-
lar areas of five different extents around the sampling plots. For each taxon the
species richness was modelled with each individual landscape variable at each
scale as the predictor, based on a linear mixed model using the software R (R
Development Core Team, 2008). Additionally, we tested the performance of sets
of three landscape-structure variables as predictors of species richness, using AIC
to compare sets composed by different methods such as expert knowledge, several
methods of ordination (see previous case study or Schindler, Poirazidis, & Wrbka,
2008), decision trees, random choice, and optimal sets after testing all possible
combinations.
In this study, landscape metrics proved to be good indicators of species richness
regarding the taxa woody plants, orthopterans, reptiles and for overall biodiversity.
Metrics regarding patch shape, proximity, texture and diversity resulted frequently
in significant univariate models, while metrics regarding similarity or edge con-
trast hardly contributed to significant models. Our results revealed that the scale
affected the performance of landscape metrics. Woody plants, orthopterans and birds
were better predicted at smaller scales, while reptiles were predicted best at larger
scales. Regarding the different methods of composing sets, optimal sets performed
always significantly better than all other methods. The statistical methods performed
slightly better than random choice, while the expert knowledge performed slightly
worse than random. The revealed pattern of relations and performances will be
useful to understand landscape structure as driver and indicator of biodiversity,
and to improve management decisions in Mediterranean forests and similar mosaic
landscapes.
13.7 Case Study 5 - Development of a Geographic Information
System for Territory Analysis of Raptor Species
Dadia National Park is well known for its high diversity of breeding birds of prey,
a community in total exceeding 300 territories (Poirazidis et al., 2010a). An inte-
grated monitoring plan was implemented by WWF - Greece in 1999, aiming at
the effective conservation of biodiversity and ecological values of the area. In this
case study
6
we describe the development of a GIS approach to estimate the terri-
tories of breeding raptors. All raptors within 34 permanent plots were counted and
each plot was censused five times during the breeding seasons 2001-2005. Raptor
observations were labelled in GIS, showing flight trajectories, possible nest sites,
the number of synchronously observed individuals, age, sex, and different terri-
torial activities under different symbols to enable analyses that consider all the
information obtained in the field. The progressive analysis per species was based
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