Ecography ECOG-03039Kaszta, Ż., Cushman, S. A., Sillero-Zubiri, C., Wolff, E. and Marino, J. 2017. Where buffalo and cattle meet: modelling interspecific contact risk using cumulative resistant kernels. – Ecography doi: 10.1111/ecog.03039

Supplementary material

Appendix1Table A1. Data used in the study with the data source

Data Source

Vegetation N content and

biomass maps based on

RapidEye imagery

Ramoelo A, Skidmore AK, Cho M a., et al

(2012) Regional estimation of savanna grass

nitrogen using the red-edge band of the

spaceborne RapidEye sensor. Int J Appl Earth

Obs Geoinf 19:151–162

Vegetation N content and

biomass maps based on

WorldView-2 imagery

Ramoelo A, Cho M a., Mathieu R, et al (2015)

Monitoring grass nutrients and biomass as

indicators of rangeland quality and quantity

using random forest modelling and

WorldView-2 data. Int J Appl Earth Obs

Geoinf 43:43–54

Altitude data from Digital

Elevation Model (DEM) based

on SRTM 4.1

Jarvis A, Reuter HI, Nelson A, Guevara E

(2008) Hole-filled SRTM for the globe Version

4, International Centre for Tropical Agriculture

(CIAT), Available at: http://srtm.csi.cgiar.org.

Land cover from WorldView-2

image classification

Kaszta Ż, Van De Kerchove R, Ramoelo A,

Cho MA, Madonsela S, Mathieu R, Wolff E

(submitted for publication) Seasonal separation

of African savanna components using

WorldView-2 imagery: a comparison of pixel-

and object-based approaches and selected

classification algorithms

Map of vegetation types based

on geological substrate and soil

Mucina L, Rutherford MC (2006) The

vegetation of South Africa, Lesotho and

Swaziland. Strelitzia, Cape Town

Table A2. Composition and buffalo movement costs for stray buffalo for each land cover class in communal areas during the wet season.

Land cover

class

Protected

areas (%)

Available in

communal

areas (%)

Used by

stray

buffalo (%)

Used to

available

ratio

Scenarios of maximum

cost

50 100 200

Bare soil 6.14 5.61 0.02 0.36 45 90 180

Crops 0 7.37 0.2 2.71 1 1 1

Grassland 18 28.60 0.03 0.10 50 100 200

Open

woodland 44.10 21.57 0.55 2.55 4 7 13

Forest 17.96 8.42 0.04 0.48 43 86 171

Thickets 2.93 8.56 0.09 1.05 32 64 128

Urban 0.04 16.08 0.02 0.12 50 99 198

Water 1.16 0.28 0 0 50 100 100

Water 100m

buffer 9.69 3.52 0.05 1.42 25 50 99

Table A3. Composition and buffalo movement costs for stray buffalo for each land cover class in communal areas during the dry season.

Land cover

class

Protected

areas (%)

Available in

communal

areas (%)

Used by

stray

buffalo (%)

Used to

available

ratio

Scenarios of maximum

cost

50 100 200

Bare soil 6.54 10.57 0.02 0.19 49 98 197

Crops 0 7.37 0.20 2.71 22 43 85

Grassland 8.5 26.91 0.03 0.11 50 100 200

Open

woodland 58.14 23.48 0.55 2.34 26 51 102

Forest 6.61 9.17 0.04 0.44 46 93 186

Thickets 10.93 5.21 0.09 1.73 32 65 129

Urban 0.04 16.08 0.02 0.12 50 100 199

Water 0.97 0.13 0 0 50 100 200

Water 100m

buffer

8.28 1.08 0.05 4.62 1 1 1

Table A4. Number of cattle herds per village and season in the study area from census data (data source: Mpumalanga Veterinary Services).

Village Cattle herds

Dry season 2012 Wet season 2013

Belfast 73 75

Huntington 80 81

Justicia 97 101

Lillydale 126 128

Somerset 79 79

Table A5. Coefficients of fixed effects from the best model predicting variations in habitat use intensity by buffaloes. The coefficients of vegetation classes are calculated in relation to class “granite”.

Predictor β SE 95 % confidence

interval

Intercept -19.58 0.24 -20.19 -18.97

Biomass -0.21 0.03 -0.26 -0.15

N 0.30 0.03 0.24 0.36

N2 0.02 0.01 0.01 0.04

Distance to water -0.09 0.02 -0.12 -0.05

Altitude 0.27 0.03 0.22 0.33

Altitude2 -0.06 0.01 -0.08 -0.04

Delagoa Lowveld 0.32 0.12 0.09 0.55

Tshokwane-Hlane

Basalt Lowvelt 0.52 0.11 0.30 0.74

Gabbro Grassy

Bushveld 0.39 0.12 0.15 0.62

Northern Lebombo

Bushveld 0.51 0.13 0.25 0.77

Biomass*altitude 0.07 0.01 0.04 0.10

Biomass*distance to

water -0.19 0.02 -0.24 -0.14

N*distance to water 0.24 0.02 0.19 0.29

Table A6. Coefficients of fixed effects from the best mixed-effect model predicting variations in habitat use intensity by cattle in wet season. The coefficients of land cover classes are calculated in relation to class "bare soil"

Predictor β SE 95 % confidence

interval

Intercept -17.31 0.12 -17.65 -16.99

Burnt areas -0.04 0.09 -0.22 0.13

Grass 0.09 0.05 -0.001 0.18

Shrubs 0.01 0.06 -0.11 0.12

Trees 0.32 0.05 0.22 0.42

Altitude -0.004 0.02 -0.05 0.04

Altitude2 0.13 0.01 0.10 0.15

Distance to water -0.04 0.01 -0.07 -0.01

Distance to settlements -0.02 0.01 -0.05 0.002

N -0.05 0.02 -0.08 -0.01

N2 -0.04 0.01 -0.06 -0.02

Biomass -0.03 0.02 -0.07 0.006

Biomass2 0.04 0.01 0.02 0.07

N*Distance to water 0.05 0.01 0.02 0.07

Biomass*Distance to water -0.08 0.01 -0.10 -0.05

Biomass*Altitude -0.17 0.01 -0.20 -0.14

N*Altitude 0.07 0.01 0.05 0.10

Table A7. Coefficients of fixed effects from the best model predicting variations in habitat use intensity by cattle in dry season. The coefficients of land cover classes are calculated in relation to class “bare soil”.

Predictor β SE 95 % confidence

interval

Intercept -16.95 0.12 -17.26 -16.63

Burnt areas -0.18 0.06 -0.29 -0.07

Grass -0.16 0.05 -0.26 -0.06

Shrubs -0.25 0.07 -0.38 -0.122

Trees -0.02 0.05 -0.13 -0.09

Altitude -0.12 0.02 -0.16 -0.09

Altitude2 -0.07 0.01 -0.09 -0.05

Distance to water -0.20 0.01 -0.22 -0.18

Distance to settlements -0.07 0.01 -0.09 -0.04

N 0.07 0.01 0.05 0.09

N2 0.01 0.01 -0.0003 0.02

Biomass 0.02 0.01 -0.02 0.05

Biomass2 -0.02 0.01 -0.04 -0.002

Biomass*Distance to

water 0.11 0.01 0.09 0.13

Biomass*Altitude 0.11 0.01 -0.13 -0.09

N*Altitude -0.04 0.01 -0.06 -0.02

Table A8. Correlation values and average absolute difference between scenarios.

CORRELATION

Null with fence dry

Null with fence wet

Null no fence dry

Null no fence wet

Dif. beh. cost 50 dry

Dif. beh. cost 50 wet

Dif. beh. cost 100 dry

Dif. beh. cost 100 wet

Dif. beh. cost 200 dry

Dif. beh. cost 200 wet

Same beh. cost 50 dry

Same beh. cost 50 wet

Same beh. cost 100 dry

Same beh. cost 100 wet

Same beh. cost 200 dry

Same beh. cost 200 wet

AV

ER

AG

E D

IFFE

RE

NC

E

Null with fence dry – 1,00 0,50 0,47 -0,10 0,54 -0,16 0,02 -0,10 0,04 0,31 0,34 0,09 0,20 -0,03 0,17

Null with fence wet 14,47 – 0,52 0,50 -0,12 0,54 -0,19 0,00 -0,13 0,01 0,28 0,34 0,05 0,21 -0,09 0,17

Null no fence dry 17,23 31,70 – 0,97 -0,14 0,63 -0,24 0,12 -0,17 0,09 0,51 0,61 0,18 0,37 -0,11 0,25

Null no fence wet 6,21 12,99 18,71 – -0,05 0,69 -0,23 0,17 -0,20 0,06 0,53 0,68 0,19 0,45 -0,14 0,27

Dif. beh. cost 50 dry 1077,95 1063,47 1095,18 1076,46 – 0,33 0,83 0,76 0,52 0,30 0,66 0,45 0,81 0,55 0,77 0,28

Dif. beh. cost 50 wet 748,59 734,12 765,82 747,11 342,32 – 0,12 0,50 0,04 0,26 0,80 0,94 0,56 0,81 0,22 0,52

Dif. beh. cost 100 dry 1221,23 1206,75 1238,46 1219,74 143,28 474,00 – 0,55 0,80 0,24 0,48 0,24 0,66 0,32 0,85 0,13

Dif. beh. cost 100 wet 1172,46 1157,99 1189,69 1170,98 112,39 424,54 74,28 – 0,34 0,66 0,70 0,56 0,82 0,71 0,59 0,48

Dif. beh. cost 200 dry 1266,25 1251,77 1283,48 1264,76 597,34 517,76 45,02 94,74 – 0,26 0,29 0,13 0,43 0,20 0,68 0,19

Dif. beh. cost 200 wet 1271,92 1257,44 1289,15 1270,43 194,25 523,33 54,98 99,46 12,42 – 0,37 0,27 0,46 0,35 0,38 0,40

Same beh. cost 50 dry 668,91 654,43 686,14 667,42 409,04 105,47 552,32 503,55 597,34 603,01 – 0,85 0,88 0,73 0,59 0,43

Same beh. cost 50 wet 711,11 696,64 728,34 709,63 368,31 74,70 510,12 461,35 555,13 560,80 96,38 – 0,62 0,83 0,31 0,50

Same beh. cost 100 dry 1056,85 1042,38 1074,08 1055,37 91,01 311,77 164,38 117,05 209,40 215,07 387,94 345,74 – 0,69 0,79 0,41

Same beh. cost 100 wet 1109,90 1095,42 1127,13 1108,41 127,23 362,19 129,43 70,51 157,05 162,09 440,99 398,78 105,48 – 0,41 0,71

Same beh. cost 200 dry 1224,52 1210,05 1241,75 1223,04 146,59 476,10 32,40 70,48 41,72 48,55 555,62 513,41 167,67 123,44 – 0,28

Same beh. cost 200 wet 1267,45 1252,98 1284,68 1265,97 189,50 518,86 56,98 95,11 15,98 6,51 598,54 556,34 210,60 157,55 47,90 –

Appendix 2 Figure A1. Buffalo-cattle contact risk maps for null scenarios with and without the fence effect, across seasons.

Figure A2. Buffalo-cattle contact risk maps for scenarios with consistent buffalo behaviour inside and outside the protected areas in wet season and for various maximum resistance values.

Figure A3. Buffalo-cattle contact risk maps for scenarios with consistent buffalo behaviour inside and outside the protected areas in dry season and for various maximum resistance values.

Figure A4. Buffalo-cattle contact risk map for scenarios with different buffalo behaviour inside and outside the protected areas in wet season and for various maximum resistance values.

Figure A5. Buffalo-cattle contact risk map for scenarios with different buffalo behaviour inside and outside the protected areas in dry season and for various maximum resistance values.

Figure A6. Matrix of averaged relative differences and correlation between each scenario.

N-null, F-fence, NF-no fence, DB-different behaviour, SB-same behaviour, W-wet, D-dry,

number indicates the maximum resistance value.