The Scale Invariance vs Non-Scale Invariance in ...

The Scale Invariance vs Non-Scale Invariance in Landscape Analysis and Biogeodiversity Studies Juan José Ibáñez, Rufino Pérez‐Gómez,  Enrico Feoli, Cecilio Oyonarte go against… We will travel to the far southeastern Sorry by my functional deafness 

Almeria Province

A dispute with archaeologists: Ostrich eggs

Almeria Province

Aridic Regime USDA-ST

Almeria Province: Syntaxonomic  approach

Almeria Province: Soil, Water, Plants Landscape, Ramblas and Wadi

Sierra Nevada Mountain Range

Almeria Province

Ramblas Low-lying cliffs wide and flat river bed & the channel narrows

Almeria Province: Soils, Plants and Water Braided streams

waterholes

leeward

Almeria Province

aquifer aquitard aquifuge

Almeria Province Leptosols Regosols Arenosols Cambisols Luvisols Solonchaks Gypsisols Calcisols

Almería Properties of Georeferenced databases analysed

Almeria Province: two sampling designs: Drainage basins: from the sea to the high mountain tops crossing from the bottom to the top reaching fast the steepest slopes Bioclimate belts: fringes roughly parallel to the coastline and the high mountains ranges

Georeferenced data bases  Potential Vegetation Analysis 

Richness

Scale Map

Nº Polygons

(40) 42, 44

1: 10.000

Soils Major Soil Groups

20

1:100.000

Soil Types (2nd

44

1:100.000

Soil associations

302

1: 100.000

3566

Lithological Units

32

1: 400.000

355

Lithological associations

17

1: 400.000

19**

1: 400.000 

Drainage Basis

WRB level)

(*) drainage delineations were supervised using Google Earth.  

6749

19

Almeria Province

Almeria Province

Almeria Province Richness 4,9 10,3 8,3 9

Lithological associations

Shannon Index 1,03 1,88 1,66 1,43

3 ln S

Lithological Units Hortonian Rank 1 Hortonian Rank 2 Hortonian Rank 3 Hortonian Rank 4

2 1

y = 0,2022x + 0,7953 R² = 0,5658

0 0

2

4

6

8

10

ln A

Potential natural vegetation Richness (S)

4

Shannon Index (H’)

3 6,9 10 12,7 24

1,07 1,23 1,57 1,86

ln S

Potential Vegetation Hortonian Rank 1 Hortonian Rank 2 Hortonian Rank 3 Hortonian Rank 4

2 y = 0,2857x + 0,6769 R² = 0,6421

1 0 0

2

4

6

8

10

ln A (Basins Area)

Soil types Richness 11,8 20,7 23,3 29,0

Shannon Index 1,73 2,06 2,14 2,35

4 3 ln S

Soils Hortonian Rank 1 Hortonian Rank 2 Hortonian Rank 3 Hortonian Rank 4

2

y = 0,3259x + 1,0235 R² = 0,7703

1 0 0

2

4

6

ln A (Basins Area)

8

10

Almeria Province

Almeria Province

Almeria Province Table 6. Correlation Matrix of the variables analyzed in the study area   

Basins 

Basins  Lithology (S)  Vegetation (S)  Soils (S)  2 Km

Lithology (S)  Vegetation (S) 

1 * 0,66 ** 0,79 ** 0,76 0,75**

1 * 0,47 ** 0,74 ** 0,76

Soils( S) 

1 ** 0,81 ** 0,77

2

Km  

1  ** 0,94  

1

Spearman's correlation coefficient or Spearman's (*) P = 0,05: (**) P = 0,01

Lithology Soils Vegetation

System Temperature

Matrix Fill %

23,7 17,5 21,4

38,0 34,6 23.0

Category/Richness Dominant Abundant Frequent Minorities Endemic Idiosyncratic Other types

Lithotypes 1 (5,9%) 4 (23,5%) 0 0 4 (23,5%) 5 (29,4%) 6 (35,3)

P for the system temperature No > 99.9% > 95.0%

Pedotypes 5 (11,4%) 2 (4,5%) 6 (13,6) 8 (18%) 3 (6,8%) 15 (34,1%) 13 (29,5%)

P simulation Run 56,74ºC 64,18ºC 52.71ºC

Vegetation types 0 (0%) 2 (5%) 3 (7,5) 8 (20%) 13 (30%) 22 (55%) 12 (30%)

Almeria Province: Climate Belts Bioclimate belts Oromediterranean Supramediterranean (upper) Suprramediterranean (lower) Mesomediterranean (upper) Mesomediterranean (lower) Thermomediterranean (upper) Thermomediterranean (lower)

Syntaxonomy Geobotany Plant  Associations

Area Km2 1.0 52.6 500.1 1909.2 2617.6 2072.3 1607.1

Berberido hispanicae‐Querceto rotundifoliae sigmetum:  Betic Upper‐Mediterranean dry‐subhumid on soil rich nutrients of the  evergreen oak (Quercus rotundifolia) Upper‐Mediterranean dry‐subhumid on soil rich nutrients serie

Soil & Parent Materials related PNV siliceous soils series nutrients rich soils  series Limestone serie edaphohygrophilous serie limestone‐dolomitic edaphoxerophilous serie nutrient soils rich edaphohygrophilous  serie siliceous soils edaphohygrophilous  serie meso‐halophytic edaphohygrophilous serie nutrient rich soils rich edaphohygrophilous microgeoserie meso‐halophytic edaphohygrophilous microgeoserie hyper‐halophytic edaphohygrophilous microgeoserie

meso‐halophytic edaphohygrophilous microgeoserie siliceous soils riparian geoserie riparian geoserie nutrient soil rich  edaphohygrophilous   geoserie Edaphoxerophilous on gypsum vegetation complex Gypifeous edaphoxerophilous vegetation complex Subsaline marls  polyteselar edaphoxerophilous c.  Halophytic coastal Vegetation Coastal Dunes & Sand deposits Vegetation Brackish waters Edaphohygrophilous geoserie Salt marshes & Salinas Vegetation

Almeria Province 3,5 3 2,5 2 1,5

y = 0,4002x ‐ 0,0522 R² = 0,9908

1 0,5 0 ‐0,5 0

2

4 6 ln Area Climate Belts

8

10

Soil Richness‐Area  by Climate Belts ln numer of soil Richness

ln Potential Vegetation Richness

Vegetarion Richness‐Area by Climate  Belts

4 3,5 3 2,5 2 1,5 1 0,5 0

y = 0,1806x + 1,9816 R² = 0,9505 0

2

4

6

ln Area of Climate Bellt

8

10

Almeria Province BB NP

BB (km2)

Soils NP

Soils (km2)

Soils S

Soils H'

PNV Nº Polygons

PNV (km2)

PNV S

Upper Thermomediterranean

2 23 58 314 641 578

0.11 52.8 500.57 1910.4 2618.1 2074.2

4 54 205 648 904 775

0.1 52.6 500.1 1909.1 2617.6 2072.3

7 16 21 26 26 30

1.28 2.03 2.1 2.16 2.19 2.19

2 10 119 964 1574 1458

0.11 52.7 498.4 1439.2 2072.2 1732.0

2 4 13 21 25 20

0.22 0.33 1.11 1.4 1.97 1.86

Low Thermomediterranean

298 1612.9

976

1607.1

34

2.36

2622

1137.6

18

1.69

Climate Belt (BB) Oromediterranean Upper Supramederranean Low Supramediterranean Upper Mesomediterranean Low Mesomediterranean

PNV H'

BB = Climate belts; NP = Number of Polygons

System Temperature Soils Vegetation

Matrix Fill %

P for the system temperature 22.72 44.8 No 32.25 33,3 No Nested subset analysis by bioclimatic belts

P simulation Run 50.27ºC 48.44ºC

Climate belts doubtful nesting, unlike for watersheds

Almeria Land Cover PNV

Area km2

Climatophilous

Lithological

Edaphophylous

Total

3463.81

2980.36

488.06

6932.24

2819

1335

1710

5864

Dominant

0

0

0

0

Abundant

0

1

0

1

Common

0

3

1

4

Frequent

6

2

2

10

Rare

1

1

10

12

Endemic

0

3

10

13

Nº polygons

(*) climatophilous: PNV climate dependant ; (*) Lithological PNV parent material dependant; (*) Edaphophylous PNV soil taxa dependant

Almeria: Land Cover 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0

 % landcover Plant Communities (soils) % Landcover  Plant comminities (lithology) % Landcover  Plant comminities (Climate)

Oromediterranean Upper Supramederranean Low Supramediterranean Upper Mesomediterranean Low Mesomediterranean Upper Thermomediterranean Low Thermomediterranean

% land cover Plant Communities (soils)

% Land cover Plant communities (lithology)

% Land cover Plant communities (climate)

0 0

100 100

0 0

0

99.7

0.3

3.2

96.7

0.1

10

30

60

17.1

1.1

81.8

13

0.01

87.0

% of Land Cover by Potential Vegetation conditioned by soils, lithology and climate

Almeria Province: PNV diversity 16 14 12 10

Total

8

Climate

6

Rock

4

Soil

2 0

Nº PNV Macro‐types

PNV dependent properties Soil Rocks Climate

58.5% 24.5% 17%

Total

Dominant Abundant Common Frequent Rare Endemic

0 1 4 9 12 15

Climate

0 0 0 6 1 0

Rock

Soil

0 1 3 1 1 4

0 0 1 2 10 11

Protected Areas and natural Parks 

•

PNV

• PNV

• • •

Biodiversity Soil: 58.5% Rocks: 24.5% Climate: 17%

Landscape • Climate: 50% • Rocks: 43% • Soils: 7%

Smallest Polygon = 0.01 m2

Almeria Province: Rank Abundance plots and Power Fits of Polygons Number vs area

500000000

All PNV Polygons: Rank Abundance Plot

450000000

Polygons Area

400000000 350000000 300000000 250000000 200000000 150000000 100000000 50000000 0 0

1000

2000

3000

4000

5000

6000

7000

Nº Polygons

Power Fit: Polygons Area Ln Area of Each Poygons

30 25 20 15 10 5 0 ‐5 ‐10

0

2

4

6

Ln Nº Polygons

8

PNV Power Fit Nº Polygons Powe Fit Gypifeous edaphoxerophilous vegetation complex 3 Minority Edaphoxerophilous on gypsum vegetation complex 37 Yes Subsaline marls  polyteselar  edaphoxerophilous vegetation complex 77 Yes Coastal Dunes & Sand deposits Vegetation 410 Yes Brackish waters Edaphohygrophilous geoserie 1 Endemic Meso‐Mediterranean on nutrient soil rich  edaphohygrophilous   geoserie 91 Yes Thermo‐Mediterranean  on nutrient rich soils rich edaphohygrophilous geoserie 667 Yes Upper‐Meso‐Mediterranean on siliceous soils riparian geoserie 33 Yes  Thermo‐Mediterranean semiarid riparian geoserie 3 Minority Oro‐Mediterranean  on nutrient rich soils rich edaphohygrophilous microgeoserie 2 Minority Thermo‐Mediterranean hyper‐halophytic edaphohygrophilous microgeoserie 54 Yes Thermo‐Mediterranean  meso‐halophytic edaphohygrophilous microgeoserie 7 Yes Salt marshes & salinas Vegetation 140 Yes Meso‐Thermo‐Mediterranean meso‐halophytic edaphohygrophilous serie 9 yes Meso‐Mediterranean on sandy siliceous soils edaphohygrophilous  serie 23 Yes Meso‐Upper‐Mediterranean sub‐humid & humid edaphohygropilous serie 13 Yes Meso‐Upper‐Mediterranean subhumid & humid  on nutrient soils rich edaphohygrophilous   serie 9 Yes Upper‐Meso‐Mediterranean dry‐ sub‐humid  on siliceous soils edaphohygrophilous serie 3 Minority Thermo‐Meso‐Mediterranean edaphohygrophilous serie 66 Yes Thermo‐Meso‐Mediterranean on nutrient rich soils rich edaphohygrophilous serie 25 Yes Upper‐Meso‐Mediterranean  on nutrient rich soils rich edaphohygrophilous serie 31 Yes 320 Yes Meso‐Mediterranean on nutrient soils rich serie Meso‐Medierranean dry on nutrient soils rich serie 517 Yes Meso‐Mediterranean semiarid serie 201 Yes Meso‐Upper‐Mediterranean‐Low limestone‐dolomitic  edaphoxerophilous serie 5 Yes Oro‐Mediterranean on nutrients rich soils  serie 10 Yes Oro‐Mediterranean on siliceous soils serie 35 Yes Upper‐Mediterranean on nutrients rich soils serie 8 Yes Upper‐Mediterranean dry‐sub‐humid  on nutrient rich soils serie 20 Yes Upper‐Meso‐Mediterranean limestone serie 1 Endemic Upper‐Meso‐Mediterranean siliceous soils Serie 353 Yes Upper‐Meso‐Mediterranean sub‐humid & humid on nutrients rich soils  serie 3 Minority Thermo‐Mediterranean‐low semiarid serie 936 Yes Thermo‐Mediterranean  Semiarid & arid costal serie 52 Yes Thermo‐Mediterranean dry & subhumid on nutrient soils rich serie 68 Yes Thermo‐Mediterranean  semiarid serie 497 Yes 724 yes Thermo‐Mediterranean semiarid‐arid serie Thermo‐Mediterranean  semiarid‐dry serie 405 Yes Thermo‐Meso‐Mediterranean serie 4 Minority Halophytic coastal Vegetation 1 Endemic All Polygons 5864 Yes

10

y = ‐2,2236x + 27,113 R² = 0,8527

R2 Z value 0.996 8.88 0.86 2.21 0.97 2.34 0.91 2.66 0.81 0.88 0.97 0.95

1.62 1.57 1.58 0.6

0.91 0.9 0.97 0.79 0.9 0.76

1.56 4.03 2.14 1.44 0.84 1.13

0.86 0.98 0.91 0.92 0.66 0.95 0.97 0.96 0.95 0.82 0.94 0.64 0.88

0.5 0.54 1.67 1.61 2.62 2.48 1.62 2.15 3.33 2.18 3.98 2.47 3.12

0.96 0.99 0.89 0.94 0.97 0.97 0.95 0.94 0.63

2.45 0.75 1.61 3.09 2.79 2.29 1.94 2.27 1.48

0.85

2.22

Almeria PNV Main Types Power Fit PNV Main Types Polygon sizes edaphohygrophilous Salt Series Sand  % Sand Dunes Salinas edaphoxerophilous Eutric Dystric gypifeous Series Subsaline marls Climatophilous Caliciculous Salt marshes

Powe Fit Yes Yes Yes Yes No No No No No No Endemic Minority

R2

Z value 0.88 0.79 0.5 0.47 0.0002 0.05 0.04 0.07 0.06 0.004

edaphohygrophilous

0.46 0.23 0.26 0.22 0.002 0.07 0.06 0.05 0.05 0.02

80 60 40

edaphohygrophilous

20 0 0

100000000 200000000

PNV edaphohygrophilous 6 5

PNV Climatophilous

4 3

6

y = ‐0,0179x + 3,5425 R² = 0,0039

4

edaphohygrophilous

2 1

y = ‐0,4614x + 9,066 R² = 0,8788

0

2

0 0 0

5

10

15

20

5

10

15

20

Edaphophylous Polygon Size 7000 6000 5000 4000 3000

Area

2000

Area%

1000 0 Total Area

Acumulated Area Acumulated Area before the before the 2nd larguer larguer edaphophylou edaphophylou polygon polygon

Relative edaphopylous polygon size

Area Km2 Area%

Total Area (Almería)

6932.24

100

Accumulated Area before the larger edaphophylous polygon

4746.21

68.5

Accumulated Area before the 2nd larger edaphophylous polygon 5674.76

87.4

PNV Larger Polygons  Climatophilous Lithological Climatophilous Lithological Lithological Lithological Lithological Climatophilous Lithological PNV Smaller Polygons  Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes Sands and Sands dunes

Area m2 466495705.5 301636684.6 252097306.5 229981736 213517556.4 186887649.8 166817685.2 154407521.4 135989448.1 Area m2 4.03736 3.739154 3.562533 3.125016 2.748981 1.4055 1.19722 0.614673 0.219602 0.010441

Almeria PNV Main Types Power Fit PNV Sands and Sand Dunes

Salty PNV Ln Rank

2,5

2,5

2

2 Sand Dunes

1,5

Ln Rank

1

1

Lineal (Sand Dunes)

0,5 0 ‐0,5

1,5

0

5

10

15

20

Lineal (Ln Rank)

0,5

y = ‐0,2301x + 4,3005 R² = 0,7939

0 0

y = ‐0,2627x + 4,4029 R² = 0,4934

5

10

PNV Eutric

15

20

PNV Dystric

4

3,5 3

3

2,5 Eutric

2

Lineal (Eutric) 1

2

Dystric

1,5

Lineal (Dystric)

1

0 0

5

10

15

y = ‐0,0749x + 3,8125 20 R² = 0,047

0,5 0 0

5

10

15

y = ‐0,0555x + 3,0349 R² = 0,0429 20

PNV & Associated soils in risk of Extinction PNV in Risk of Extinction 

 

Nº  Polygons  Conservation 

Max  Min  Min Km2  Km2  m2 

Gypiferous edaphoxerophilous vegetation complex 

3 

Minoritiy 

7.289  0.004 

4099 

Brackish waters Edaphohygrophilous geoserie

1 

Endemic

0.058

Thermo‐Mediterranean semiarid riparian geoserie 

3 

Minoritiy 

0.299  0.158 

157791 

Oro‐Mediterranean  on nutrient rich soils rich edaphohygrophilous microgeoserie 

2 

Minoritiy 

0.005  0.005 

4774 

Thermo‐Mediterranean  meso‐halophytic edaphohygrophilous microgeoserie 

7 

Risk 

2.399  0.002 

1521 

Meso‐Thermo‐Mediterranean meso‐halophytic edaphohygrophilous serie Meso‐Upper‐Mediterranean subhumid & humid  on nutrient soils rich edaphohygrophilous   serie 

9 

Risk

0.198

0.011

9886

9 

Risk 

0.076  0.019 

19020. 

Upper‐Meso‐Mediterranean dry‐ sub‐humid  on siliceous soils edaphohygrophilous serie 

3 

Minoritiy 

0.041  0.022 

22251 

58082

Meso‐Upper‐Mediterranean‐Low limestone‐dolomitic  edaphoxerophilous serie

5 

6.657

0.051

50618

Upper‐Mediterranean on nutrients rich soils serie 

8 

2.294  0.003 

3295 

Upper‐Meso‐Mediterranean limestone serie 

1 

Endemic 

Upper‐Meso‐Mediterranean sub‐humid & humid on nutrients rich soils  serie 

3 

Minoritiy 

Thermo‐Meso‐Mediterranean serie

4 

Halophytic coastal Vegetation 

1 

0.020  0.024  0.010  6.406

Endemic 

20799 

4.155 

0.519

10461  518558 4155390 

Spain (Iberian Peninsula)

Spain (Iberian Peninsula)

J1

Tectonic Depressions

Spain nesting impossible For each basin does exist nesting

Diapositiva 31 J1

Juanjo; 09/05/2015

Spain (Iberian Peninsula) 120000

Rank Abundance Plot Spain

80000 60000 40000 20000 0 0

5

10

15

20

25

30

Basins Area in km2 120000

Rank Abundance Plot Iberia 

100000 24 higest basins

24 higest basins

100000

80000 60000 40000 20000 0 0

5

10

15

20

Bains Area in Km2

25

30

35

Spain (Iberian Peninsula) Basins Rank

Soil S

Soil H´

PNV S

PNV H´

Geology S

Geology H´

Quaternary Landforms S

Quaternary Landforms H

Rank 1

7.12

1.37

2.41

0.42

2.91

0.65

2.65

0.56

Rank 2

10.47

1.61

3.18

0.58

4.08

0.98

2.99

0.63

Rank 3

11.40

1.75

4.86

0.88

5.22

1.12

4.11

0.80

Rank 4

17.90

1.97

9.44

1.43

9.00

1.42

7.38

1.38

Rank 5

29.67

2.29

14.33

1.44

15.33

1.96

24.67

2.31

Rank 6

32.6

2.43

31.20

2.31

16.80

1.98

26.60

2.19

30

Area‐Basins Rank

Area KM2

25 20 15 10 5

y = 3,7746x + 17,284 R² = 0,8881

0 0

0,5

1 Basins Rank

1,5

2

Spain (Iberian Peninsula) Basins  Rank

Soil  Types

PNV  Types

Lithological  Association Types

Basins Hortonian  1 Rank Soil types 99.6%* 1 PNV Types 95.0%* 0.99.5* 1 Lithological  98.6%* 99.8%* 77.3% 1 Associations Quaternary Units 95.1%* 99.9%* 58.7% 84.3% Correlation Matrix Aggregated Data  (T‐Student  >95% = (*)) Basins/ Samples All  100km2  200km2 Samples Samples Soils R2 Values 0.46 0.51 0.55 2 Quaternary R 0.59 0.59 0.65 Values 0.45 0.54 0.57 PNV R2 Values Lithological 0.50 0.38 0.38 Assoc R2 Values R2 Taxa-area relationships Values deleting small basins

Quaternary  Units

1

conflictive overlapping of thematic maps -Small effect islands -Sampling Density

Spain (Iberian Peninsula) conflictive overlapping of -Small effect islands By drainage basins thematic maps -Sampling Density

4 3,5 3 2,5 2 1,5 1 0,5 0

Soil Types‐Area

PNV‐Area ln Richness

4

y = 0,8664x + 1,8007 R² = 0,8921

3 2 y = 1,3576x + 0,5054 R² = 0,8579

1 0

0

0,5

1

1,5

0

2

0,5

ln Basins Rank

3

ln Richness

2 1,5 1 y = 1,0313x + 0,8482 R² = 0,9024

0,5 0 0,5

1 ln Basins Rank

1,5

2

Quaternary Landforms

3,5 3 2,5 2 1,5 1 0,5 0

y = 1,3652x + 0,4973 R² = 0,7703 0

0

1 ln Basins Rank

Lithological Ass.

2,5 ln Richness

ln Soil types

Spain (Iberian Peninsula) By drainage basins

1,5

2

0,5

1 ln Basins Rank

1,5

2

Spain (Iberian Peninsula) Density Power law Fit R2 Z value

Lithology

Quaternary Vegetation Pedotypes landforms (PNV) Spain

0.63 0.55

0.50 0.62

0.64 0.63

0.63 0.64

Pedotypes Iberian Peninsula 0.77 0.90

Density = richness per unit area Geology 

  

Basin number  4007  Muga  4009  Fluvia  4004  Deva  4003  Sella  4005  Nervión  4019  Andarax 4017  Odiel  4001  Navia  4006  Ulla  4008  Ter 4020  Guadalhorce  4021  Guadalete  4014  Mijares  4002  Nalón 4010  Llobregat  4013  Turia  5003  Segura  6001  Miño  5001  Jucar  5002  Guadiana  6004  Tajo  6005  Guadalquivir  6003  Duero  6002  Ebro 

 

Lager basins

Cuaternario 

  

Basin  Numer 

  

4007  4009  4004  4003  4005  4019 4017  4001  4006  4008 4020  4021  4014  4002 4010  4013  5003  6001  5001  6005  5002  6004  6002  6003 

Muga  Fluvia  Deva  Sella  Nervión  Andarax Odiel  Navia  Ulla  Ter Guadalhorce  Guadalete  Mijares  Nalón Llobregat  Turia  Segura  Miño  Jucar  Guadalquivir  Guadiana  Tajo  Ebro  Duero 

PNV  Basin  Numer

  

Pedotypes  Basin  Numer 4007  Muga  4007  4009  Fluvia  4009  4004  Delva  4004  4003  Sella  4003  4005  Nervión  4005  4019 Andarax 4019 4017  Odiel  4017  4001  Navia  4001  4006  Ulla  4006  4008 Ter 4008 4020  Guadalhorce  4020  4021  Guadalete  4021  4014  Mijares  4014  4002 Nalón 4002 4010  Llobregat  4010  4013  Turia  4013  5003  Segura  5003  6001  Miño  6001  5001  Jucar  5001  5002  Guadiana  6005  6004  Tajo  5002  6005  Guadalquivir  6004  6003  Duero  6002  6002  Ebro  6003 

      Muga  Fluvia  Deva  Sella  Nervión  Andarax  Odiel  Navia  Ulla  Ter  Guadalorce  Guadalete  Mijares  Nalón  Llobregat  Turia  Segura  Miño  Jucar  Guadalquivir  Guadiana  Tajo  Ebro  Duero 

Almeria Conclusions •

Conceptually, two sampling designs, one perpendicular to the other.

•

Both sampling designs together, provide information on all soil forming factors

•

The results are complementary not antagonistic

•

However the analysis by climate belts break the scale invariance to nested subset analysis showed using drainage basins. This result is logic (islands-area and watersheds-area follow power laws, PNV no). Spain is too heterogeneous: the conditions for structures do not occur.

•

Landscape (soilscape) spatial patterns could be considered from both perspectives: scale invariance vs non scale invariance (sampling scheme)

Almeria Conclusions: Two Sampling Designs •

Regularities – Richness-area relationships fit well to power laws – Diversity area-relationships relationships fit well to power laws – Plant communities diversity as well as pedodiversity are conform to the same patterns being correlated among them – Geological assemblages no? – The theory of island biogeography and biodiversity-area relations in continents.

•

Idiosyncrasies – Nestedness do not occurs by bioclimatic belts or for the whole of Spain. Each Phytoclimate fringe tend to have idiosyncratic soils and vegetation types. – Nesting requires that the environmental conditions are rather homogeneous This is not the case of watersheds in Spain – The information provided by drainage basin on landforms is lost in climate belts analysis. Thus soil-landforms relationships are not clear.

Almeria Conclusions: Two Sampling Designs • Limitations (shortcomings) of databases – Different scales difficult to detect regularities better – A geological map do not represent accurately lithology outcrops in earth surface systems. Geological maps do not permit quantify the extent covered by the different lithologies. thus, it is not feasible analyse the relations between parent materials, soils and plant communities diversities – Lack information on geomorphology – There is not a universal lithological classification to compare different territories – There is not a universal geomorphological classification to compare different territories – There is not a universal vegetation classification to compare different geographical spaces – Syntaxonomic approach has been used systematically across all he European continent (e.g. Habitat 20000), but is but it is practically unknown in Anglo-Saxon countries.

Almeria Conclusions Soils and Water at landscape level •

Sintaxonomic approach provide information on plant species, plant associations, climate, but also ¡on soils! (nutrients, salt contents, texture and water regimes).

•

In Almeria study area the most plant landscapes are climate & Lithological dependents

•

In Almeria biodiversity depend mainly on soils (>60%)

• • •

Soil: 58.5% Rocks: 24.5% Climate: 17%

•

Edaphohygrophilous PNV fil bet to power laws across several magnitude orders (scale invariance)

•

Soil degradation imply a huge loss of natural plant communities

•

Preserving soil-habitat we preserve above and underground diversities

Almeria Conclusions Soils and Water at landscape level and Biogeodiversity islands •

PNV map at the scale 10.000 concern to vegetation individuals and not to associations of PNV. Each polygon is an PNV individual. This fact permit the analysis of polygons without disaggregation.

•

Edaphophylous PNV polygons are very small, in general. Thus soil conditions (pedotypes) do not appear at the scale of the soil map (E1: 1000.000). Also is true that WRB 1998 and the USDA ST were carryout mainly to agronomic purposes ignoring natural preservation.

•

Some on the termed soil functions concern to biodiversity preservation (“gene pool”).

•

The most of edaphophylous series that demand considerable supply water (of edaphohygrophylous ).

Almeria Conclusions Soils and Water at landscape level and Biogeodiversity islands •

Edaphohygrophylous PNV seems islands of biogeodiversity (invisible in the soil map), into a matrix of arid lands, but providing the 58.5% of the biodiversity, following scaling laws along several orders of magnitude: both for each type of vegetation as the whole of them.

•

Many edaphohygrophylous PNV are scarce and of small size, being difficult their preservation in an arid-anthropic landscape.

•

Overlaying PNV and the soil maps should allow identify the sites of arid landscapes with edaphohygrophylous PNV. To study soilsvegetation relationships PNV map should provide a list of “phases s.l.” to conservation purposes

•

The concepts of biogeodiversity islands and islands of fertility in arid lands are not the same but are related in some aspects.

Almeria Conclusions Soils and Water at landscape level and Biogeodiversity islands •

The information provided by the PNV map should be used as phases s. l. with available to indicating sites to be preserved via complementarity methods (designing natural network of PNV/soil reserves).

•

Thus if some of the edaphohygrophylous PNV are in risk of extinction, pedological information could be used as a tool of ecological/pedological restauration.

•

Are there this spatial pattern and scale invariance of edaphohygrophylous PNV in other arid lands?

•

Biogeodiversity islands: Biopedodiversity islands

Bioclimatic Diagrams Simulation Model (González Rebollar)

The End

A landscape film of the far eastern

XIX Centurty Lead Fever

Almeria Geological History

Spain (Iberian Peninsula) PNV, Pedotypes, Geology and Quaternary

Soil Types (WRB, 1998) of the Almeria Province Soil Types 2nd WRB (1998) Calcaric Regosol Lithic Leptosol Leptic Regosol Eutric Regosol Aridic Calcisol Calcaric Cambisol Calcaric Fluvisol Eutric Cambisol Rendzic Leptosol Aridic Solonchak Haplic Calcisol Chromic Luvisol Luvic Calcisol Terric Anthrosol Epipetric Calcisol Luvic Phaeozem Eutric Fluvisol Eskeletic Arenic Fluvisol Chromic Cambisol Calcic Luvisol Dystric Regosol Leptic Phaeozem

Acronyms % Covered Soil Types 2nd WRB (1998) Acronyms % Covered RGca 27.438 Sands Mare 0.3481 LPli 14.0425 Gypsiric Regosol RGgp 0.3354 RGle 13.4096 Albic Arenosol ARab 0.2032 RGeu 10.777 Calcaric Phaeozem PHca 0.1661 CLad 5.6389 Gleyic Solonchak SCgl 0.1632 CMca 5.1564 umbric Leptosol LPum 0.1465 FLca 4.8169 Salinas Msal 0.1305 CMeu 2.1548 Aridic Arenosol ARad 0.1162 LPrz 1.9576 Dystric Cambisol CMdy 0.0904 SCad 1.8338 Aridic Gypsisol GYad 0.0754 CLha 1.6948 Hypergypsic Gypsisol GYgyh 0.0722 LVcr 1.437 Anthric Urbic Regosol RGah_ub 0.055 CLlv 1.3569 Chromic Vertisol VRcr 0.0391 ATtr 1.1867 Leptic Umbrisol UMle 0.0301 CLptp 1.1123 Water bodies Memb 0.0172 PHlv 1.0105 Gleyic Cambisol CMgl 0.0108 FLeu 0.6984 Dystric Gleysol GLdy 0.016 FLsk_ar 0.5214 Anthric Spolic Regosol RGah_sp 0.011 CMcr 0.5072 Vertic Cambisol CMvr 0.0014 LVcc 0.4589 Urban Soils Mnuc 0.0012 RGdy 0.3852 Dystric Fluvisol FLdy 0.0091 PHle 0.3664 Calcic kastanozem KScc 0.0007

Nº Soil Types/RSG including other sources RSG

Nº Soil Types

% Covered

Nº Soil Types

Nº Soil Types

% Covered

Nº Soil Types

Regosols

7

52.1

11 Umbrisols

1

0.27

1

Leptosols

3

16.03

6 Vertisols

1

0.1

2

Arenosols

2

10.01

2 Kastanozems

1

0.09

2

Fluvisols

4

8.04

5 Anthrosols

1

0.04

1

Cambisols

6

6.1

9 Luvisols

2

0.03

1

Calcisols

4

1.97

5 Salinas

1

0.02

1

Phaeozems

3

1.96

3 Water Bodies

1

0.018

1

Gypsisols

2

1.92

4 Sands

1

0.0009

1

Solonchaks

2

1.01

4 Urban Soils

1

0.0008

1

Gleysols

1

0.29

1 Chernozems

0

0.0004

1

44

100

62

Total  S

Other soils of Almería not included in the Soil Map

Dystric Leptosol

Leptic Cambisol

Calcaric Leptosol

Antropic-Reductic Regosol

Eutric Leptosol

Antric-Aric Regosol

Mollic Leptosol

Antric-Garbic Regosol

Hiposalic Fluvisol

Calcic Chernozem

Luvic Kastanozem

Calcic Solonchak

Calcic Gypsisol

Haplic Solonchak

Endopetrics Calcisol

Haplic Gypsisol

Mollic Cambisol

Calcic Vertisol

Endosalic Cambisol

Other Questions and Answers (Enrico Feoli)  Alpha diversity • (1) How much are  diversities of lithotypes, pedotypes and vegetation types of watersheds correlated to the extent (area) of the watersheds? • (2) How much is  pedodiversity correlated to  lithodiversity? • (3) How much is  vegetation diversity correlated to  pedodiversity and  lithodiversity?  Beta Diversity • (4) How much are the  litho-, pedo- and vegetation diversities of watersheds correlated among themselves? • (5) How much are  litho-, pedo- and vegetation diversities of watersheds correlated with the extent of the watersheds? • (6) How much are the  litho-, pedo- and vegetation diversities of watersheds correlated to the proximity of the watersheds? • (7) Is the land system of the province of Almeria classifiable in subsystems of watersheds according to lithology, pedology and vegetation, or is the nestedness overwhelming any classification possibility?

Other Questions and Answers (Enrico Feoli)  Alpha diversity Questions • We have considered the richness and the Shannon entropy (the Shannon entropy is routinely used to calculate the diversity of landscapes, of the watersheds in terms of their lithotypes, soil types and vegetation types (series) and we have applied linear and non-linear regression analysis (simple and multiple) between the area (independent variable) and the diversity measures (dependent variables). •

We have used simple correlation analysis (by Spearman and Pearson coefficients) and partial correlation analysis (first and second order partial correlation using Pearson correlation coefficient) .

•

To evaluate the best fit of the non-linear regression the program offers the sum of squares of the residuals. We used this parameter to compare different regressions and to evaluate the multiple regression in a step-wise mode to see how much the vegetation diversity–area relationship is improved by introducing in the regression, first the lithodiversity and then the pedodiversity and to see how much the relationship pedodiversity-area improves by introducing in the regression the lithodiversity

Other Questions and Answers (Enrico Feoli)  Beta Diversity Questions • Diversity questions they concern the analysis of (dissimilarities, similarity) within a set of sampling units.

the

heterogeneity

•

While  diversity is expressed by a scalar obtained from a single vector,  diversity is expressed by a scalar obtained from a matrix of at least two vectors.

•

To answer the fourth question (How much are the  litho-, pedo - and vegetation diversities of watersheds correlated among themselves? we have used the three matrices L(L,N), S(S,N) and V(V,N) and we have calculated the similarity between the watersheds considering both the area of the types (quantitative data) and the binary data for each of the three matrices. The Mantel’s test has been used to test the correlation between the similarity matrices.

Other Questions and Answers (Enrico Feoli)  Beta Diversity Questions • Diversity questions they concern the analysis of the heterogeneity (dissimilarities, similarity) within a set of sampling units. •

While  diversity is expressed by a scalar obtained from a single vector,  diversity is expressed by a scalar obtained from a matrix of at least two vectors.

•

To answer the fourth question (How much are the  litho-, pedo - and vegetation diversities of watersheds correlated among themselves? we have used the three matrices L(L,N), S(S,N) and V(V,N) and we have calculated the similarity between the watersheds considering both the area of the types (quantitative data) and the binary data for each of the three matrices. The Mantel’s test has been used to test the correlation between the similarity matrices.