Padoa schioppa fauna monitoring
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Fauna monitoring in urban
forests of Lombardy
Emilio Padoa-SchioppaUniversity of Milano-Bicocca
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Why monitoring?
«Conoscere per deliberare» (Luigi Einaudi) –
The knowledge is the starting point for any
decision
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Biodiversity surveyWe used birds as indicators of biodiversity
because:
• Ecological chains
• Linkage to environment
• Easy to contact
• Quantitave data
• Good knowledge of autoecology of
species• Flag species for many people
Methodology
• Bird point count – 10 min. / unlimited
distance / 2 times during breeding season
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BirdsNome italiano Nome scientifico Nome Inglese
Airone cenerino Ardea cinerea Grey Heron
Fagiano Phasianus colchicus Pheasant
Colombaccio Columba palumbus Woodpigeon
Rondone Apus apus Common Swift
Picchio verde Picus viridis Green Woodpecker
Picchio rosso maggiore Dendrocopus major Great Spotted Woodpecker
Rondine Hirundo rustica Swallow
Pettirosso Erithacus rubecula Robin
Usignolo Luscinia megarhynchos Nightingale
Merlo Turdus merula Blackbird
Capinera Sylvia atricapilla Blackcap
Pigliamosche Muscicapa striata Spotted Flycatcher
Codibugnolo Aegithalos caudatus Long-tailed Tit
Cinciarella Parus caeruleus Blue Tit
Cinciallegra Parus major Great Tit
Picchio muratore Sitta europaea Nuthatch
Gazza Pica pica Magpie
Taccola Corvus monedula Jackdaw
Cornacchia grigia* Corvus (corone) corone Carrion Crow
Storno Sturnus vulgaris Starling
Fringuello Fringilla coelebs Chaffinch
Cardellino Carduelis carduelis Goldfinch
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Birds
0
2
4
6
8
10
N°
of
spe
cie
s
Point count
Species turn-over
S2
Common species
S1
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Birds
0 2 4 6 8 10 12 14 16
Grey Heron
Pheasant
Spotted Flycatcher
Nuthatch
Jackdaw
Common Swift
Swallow
Robin
Blue Tit
Magpie
Goldfinch
Green Woodpecker
Long-tailed Tit
Starling
Woodpigeon
Great Tit
Nightingale
Carrion Crow
Great Spotted Woodpecker
Chaffinch
Blackcap
Blackbird
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Birds
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Insects: butterflies
and carabidsData:
29/05/20
12
10/07/2
012
01/08/201
2 23/08/2012
14/09/201
2
Species 1 2 3 4 5
Argynnis paphia (Linné, 1758) x
Celastrina argiolus (Linné, 1758) x x
Colias crocea (Geoffroy, 1785) x x
Vanessa atalanta (Linné, 1758) x
Aricia agestis ([Denis & Schiffermüller],
1775) x x x
Cupido argiades (Pallas, 1771) x x x x
Iphiclides podalirius (Linné, 1758) x
Issoria lathonia (Linné, 1758) x
Melitaea athalia (Rottemburg, 1775) x x
Ochlodes venatus (Bremer & Grey, 1853) x
Papilio machaon Linné, 1758 x
Pararge aegeria (Linné, 1758) x x x x x
Pieris brassicae (Linné, 1758) x x
Pieris napi (Linné, 1758) x x x x
Pieris rapae (Linné, 1758) x
Polygonia c-album (Linné, 1758) x x x x
Polyommatus icarus (Rottemburg, 1775) x x x
Satyrium w-album (Knoch, 1782) x
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Insects: butterflies and carabids
0
5
10
15
20
25
30
N° specie
N°
spe
cie
Carabidi
Foresta Carpaneta
Parco nord 1
Parco nord 2
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Conclusions
• Sampling protocols allow to get a good knowledge of
biodiversity
• Birds (species and abundance) appear to be linked to forest
structure
• Butterflies are linked also to landscape contest (more species
in open areas)
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Management & BiodiversityHow management decision may
influence biodiversity?
Biodiversity conservation
in urban parks
Landscape
EcosystemCommunityForest structure
Tree diversity
… … …
Area of park
Forest coverage
… … …
Landscape heterogeneity
Distance from center
… … …
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Large parks of Milano suburbs
Parks of Bari
Parks of Milano city
Cluster analysis
MI 2
MI 9MI 4
MI 12MI 10MI 7MI 13MI 6MI 11
MI 5
BA 1BA 2BA 3
MI 1MI 3
MI 8
Dendrogram using Average Linkage (Between Groups)
Rescaled Distance Cluster Combine
0 5 10 15 20 25
Sanesi et al., AUF, 2009
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y = 0,0027x + 6,3432
R2 = 0,57380
10
20
30
40
0 2000 4000 6000 8000 10000
Distanza dal centro città (m)
n° d
i sp
ecie
y = 5,4094Ln(x) + 0,2575
R2 = 0,697
0
5
10
15
20
25
30
35
40
0 100 200 300 400 500 600 700
Area (ha)
n° s
pecie
y = 0,3943x + 9,3607
R2 = 0,7802
0
10
20
30
40
50
0 20 40 60 80 100
Copertura arborea (ha)
n° d
i sp
ecie
Biodiversity and forests management
Sanesi et al., AUF, 2009
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Forest structure
?
We selected 4 targets specie
– Turdus merula
– Fringilla coelebs
– Parus major
– Serinus serinus
From literature (Massa et al., 2004;
Fornasari 2006) linked to forest structure
but present also in urban envirnoment
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Forest structure and bird abundance
DBH – min / 1° quartile / median / 3° quartile / maxAbundance of target species
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Forest structure and
bird abundance Test Statistics(a)
D min Blue tit
Mann-Whitney U 335,000
Z -,459
Asymp. Sig. (2-tailed) ,646
a Grouping Variable: CLASSE 5
Test Statistics(a)
Diametro minimo Blue tit
Mann-Whitney U 404,500
Z -,286
Asymp. Sig. (2-tailed) ,775
a Grouping Variable: CLASSE 10
Test Statistics(a)
1° quartile Blue tit
Mann-Whitney U 287,000
Z -1,771
Asymp. Sig. (2-tailed) ,077
a Grouping Variable: CLASSE 10
Test Statistics(a)
1° quartile Blue tit
Mann-Whitney U 470,500
Z -1,024
Asymp. Sig. (2-tailed) ,306
a Grouping Variable: CLASSE 20 Test Statistics(a)
mediane Blue tit
Mann-Whitney U 466,000
Z -1,598
Asymp. Sig. (2-tailed) ,110
a Grouping Variable: CLASSE 20
Test Statistics(a)
mediane Blue tit
Mann-Whitney U 371,000
Z -1,020
Asymp. Sig. (2-tailed) ,308
a Grouping Variable: CLASSE 30 Test Statistics(a)
3° quartile Blue tit
Mann-Whitney U 485,000
Z -1,040
Asymp. Sig. (2-tailed) ,298
a Grouping Variable: CLASSE 30
Test Statistics(a)
3° quartile Blue tit
Mann-Whitney U 328,500
Z -1,148
Asymp. Sig. (2-tailed) ,251
a Grouping Variable: CLASSE 40 Test Statistics(a)
Diametro max Blue tit
Mann-Whitney U 489,000
Z -1,301
Asymp. Sig. (2-tailed) ,193
a Grouping Variable: CLASSE 60
Test Statistics(a)
Diametro max Blue tit
Mann-Whitney U 292,000
Z -1,937
Asymp. Sig. (2-tailed) ,053
a Grouping Variable: CLASSE 80
Sanesi et al., AUF, 2009
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Blue tit & forest structure
Blue tit
y = 5,8371e0,0261x
R2 = 0,9995
y = 3,6159e0,0236x
R2 = 0,99250
20
40
60
80
100
0 25 50 75 100Tree n°
DBH
Minimum
Optimal
Sanesi et al., AUF, 2009