Nesting habitat selection & breeding distribution of two sympatric insular eagle populations: The Golden Eagle (Aquila chrysaetos) and the Bonelli’s Eagle (Aquila fasciata) on the island of Crete (Greece)
1Xirouchakis
Stavros, 2Solanou Maria & 1Georgopoulou Elisavet
1Natural History Museum of Crete, University of Crete, University Campus (Knossos) , Heraklion 71409, Crete, Greece 2 Biology Department, University of Crete, University Campus (Voutes), Heraklion 70013, Crete, Greece
Eagles of Palearctic: Study and Conservation II International Scientific and Practical Conference 7–10 September 2018 Park-Hotel Lake Aya, Katun village, Altai Kray, Russia
Aquila chrysaetos (6 subspecies)
nesting resident wintering
Aquila fasciata
Study area & Species Geographical isolation: 5 millions years ago Glacial period: 2,5 millions – 12.000 years ago Human presence 8.000 years ago 350 Birds (90 breeding) 18 mammals 11 reptiles 150 land snails Invertebrates (10-50% endemic) 1.600 plants
No territories Crete/ Greece
No pairs/ inds
Aquila chrysaetos
27/150
22-25/ 60-80
R
EN
Aquila fasciata
25/ 140
17-20/
EN
VU
Species
Europe
Greece
Aquila chrysaetos
Nest construction: Χ Egg-laying & incubation: 0 Egg-hatching & chick rearing: *
Aquila fasciata
Breeding & Foraging habitat
Diet
Nest site requirements
Aims
To identify the nesting areas of the species on the island of Crete To investigate the factors that affect nest-site selection To construct predictive breeding distribution maps To delineate the potential suitable nesting habitat for the species To asses nesting habitat spatial overlap & compare nest-site variables
Methods 1. Locate all eagle nest sites (fieldwork) 2. Spatial mapping of eagle nest sites (GIS geodatabase) 3. Assessment of nest-site environmental variables (GLM logistic regression model) 4. Prediction maps (Species Distribution Model) 5.
Breeding habitat overlap (Quantum, SAGA - GIS software)
6. Univariate analysis & comparison of nest-site habitat variables (R software)
Selection of environmental variables (biological meaning) Proper statistical analysis (autocorrelation) Model selection (stepwise procedure) SDM evaluation (MaxEnt)
“eagle” pixels = 400X400m grids containing an eagle nest VIFi= 1/(1-Ri2) Bioclimatic variables http://www.worldclim.org/bioclim
BIO1= Annual Mean Temperature BIO2= Mean Diurnal Range (Mean of monthly (max temp - min temp)) BIO3= Isothermality (BIO2/BIO7) (* 100) BIO4= Temperature Seasonality (s.d.*100) BIO5= Max Temperature of Warmest Month BIO6= Min Temperature of Coldest Month BIO7= Temperature Annual Range (BIO5-BIO6) BIO8= Mean Temperature of Wettest Quarter BIO9= Mean Temperature of Driest Quarter BIO10= Mean Temperature of Warmest Quarter BIO11= Mean Temperature of Coldest Quarter BIO12= Annual Precipitation (mm) BIO13= Precipitation of Wettest Month BIO14= Precipitation of Driest Month BIO15= Precipitation Seasonality (CV) BIO16= Precipitation of Wettest Quarter BIO17= Precipitation of Driest Quarter BIO18= Precipitation of Warmest Quarter BIO19= Precipitation of Coldest Quarter
Disturbance variables (DEM) dist_pop= distance from the nearest inhabited area dist_road= distance to the nearest road dist_urban= distance from the nearest urban settlement dist_water= distance from the nearest water body
Landscape variables (DEM & http://) altitude= elevation of nest site aspect= orientation of nest-site slope= % slope of the nesting cliff geo_index= rock type of nesting cliff hnv= % of “High Nature Value” farmland in “eagle” pixels landuse_index= land use type in “eagle” pixels livestock= No. of sheep & goat in “eagle” pixels
MaxEnt SDM Evaluation Area under ROC curve (AUC) ROC is Sensitivity by (1- Specificity)=(FPR)
True Positive Rate
1
AUC > 0.5 Higher Predictive Power AUC = 0.5 Random Chance AUC < 0.5 Worse than Random
0 0
False Positive Rate
Sensitivity= % of presences correctly predicted Specificity= % of absences correctly predicted
1
Results Aquila chrysaetos Coefficients:
Aquila fasciata Estimate
(Intercept)
-5.621e-01
-1.52
Slope
2.472e-02
Distance to urban areas Distance from water bodies Land use
Variable
Coefficients:
z value Pr(>|z|) 0.12772
Estimate z value Pr(>|z|)
(Intercept)
-0.313
-0.75
0.45429
2.81 0.00492 **
Altitude
-0.001
-2.42
0.0154 *
1.517e-04
1.95
0.0515.
Slope
0.034
2.89
-6.710e-04
-2.05
0.04002*
0.00386 **
Land use
-0.134
-2.13 0.03332 *
-2.042e-01
-2.78
0.0055**
Mean ± se
range
Wilcox test value (W)
P-value
Aquila chrysaetos
Aquila fasciata
Aquila Chrysaetos
Aquila Fasciata
715±44 m
372± 28 m
135-1387 m
71-912 m
428
<0.0001***
27.5±2.1
25.6±1.9
1-60
1-49
1089
0.60
Distance from urban areas
2±0.15 km
2.6± 0.24
0.4-11.7 km
0.4-10.8 km
866
0.03*
Distance from water
451±86 m
379±92m
0.1-3 km
0.1-4 km
1003
0.224
Altitude Slope
Aquila chrysaetos
AUC = 0.95
Altitude Slope Substrate Land use & HNV farmland Livestock Distance from roads (& humans) Mean Temp of Driest Quarter
Aquila fasciata
AUC = 0.93
Altitude Slope Land use Distance from roads Distance from water bodies Mean diurnal temp range
Aquila chrysaetos Aquila spp. breeding distribution
Aquila fasciata
Species
Km2
% Crete
A. chrysaetos
1282.6
15.5
A. fasciata
1900.6
23
Aquila spp.
647.2
7.8
Conclusions • • • • • • •
Both Aquila species select vertical cliffs for nesting within pastoral areas A. fasciata breeds at lower altitude & closer to the sea (prey species) A. chrysaetos selects inland mountains ( limestone substrate, livestock) Weather conditions – Rural practices (carrion, prey behaviour) Variable tolerance to human presence (territory abandonment) Habitat alteration & land use changes (agriculture, tourism, energy) Home range & space use (telemetry data)
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