Mongolia assessment March 2014: Technical note

Technical update on the Mongolia assessment carried out in March 2014
Shared with the Biodiversity Modelling Network (BMN) on Linked In

Published on 1-4-2014

Hello all,

Underneath an overview of assumptions and equations that I have been using for my latest GLOBIO3 assessment of the current biodiversity in Mongolia that I carried out early March 2014.

Land use
The land use in Mongolia is quite deviating from that of other developing countries. Over 80% of the country is used for grazing. These are natural to semi natural grasslands in a scala of different landscapes, such as mountain taiga, mountain steppe, forest steppe and desert steppe. As most current land cover and land use maps of Mongolia do not distinguish different grassland use intensities a method had to be developed to classify this land use type into different intensity classes. Therefore I created a grazing intensity map made by a combination of livestock consumption map and a fodder production map. Katalin Petz uses a similar approach in her dissertation for the Wageningen University that was published this year:

For livestock I used FAO livestock maps and national statistical data on livestock in Mongolia. First I converted the different livestock units for Cattle, Sheep and Goat into so called Sheep units and made one Sheep unit map. Secondly I used statistical data on Cattle, Horses, Camels, Sheep and Goat per province (Aimag) to correct the total sheep unit map. With data on the average yearly consumption per Sheep unit a average consumption map could be made.

In 1981 the Russians made a fodder production map for Mongolia. As the general land use in Mongolia has hardly changed over the last decades I assumed that this fodder production map is still valid.

By dividing the two maps by a raster calculation a grazing intensity map was created with 6 grazing intensity classes; 4 classes on natural rangelands: no grazing (MSA_nr = 1), light grazing (MSA_nr = 0.9), moderate grazing (MSA_nr = 0.7), intensive grazing (MSA_nr = 0.6), and two classes on degraded rangelands: very intensive grazing (MSA_nr = 0.5), and overgrazing (MSA_nr = 0.3).

This classification was used in combination with the latest global MSA rangeland table to address local MSA_land use values which are mentioned in brackets behind the local rangeland classes.

The global GLOBIO3 rangeland MSA table distinguishes 5 types of rangeland: Natural Rangeland (MSA_rl = 1), Moderately used rangelands (MSA_rl = 0.6), Intensively used rangelands (MSA_rl = 0.5), Man made grasslands (MSA_rl = 0.3) and Ungrazed abandoned rangelands (MSA_rl = 0.7).

In addition to rangeland classes the following land use types could be distinguished for Mongolia: Extensive cropland (MSA_crl = 0.3), Urban area (MSA_urb = 0.05), Natural forest (MSA_nfor = 1), Natural bare <glaciers and rock outcrop> (MSA_nb = 1) and Mining (MSA_min = 0.3).

The pressure caused by Infrastructure is calculated based on the direct pressure from roads and the indirect pressure around urban, agricultural and mining areas in Mongolia.

The width of the impact zones was set to 5 km around roads and to 10 km around the mentioned impact areas. In previous assessments an infrastructure tool was used to distinguish the impact along roads by zone and population pressure, but this methodology is not used in GLOBIO3 anymore. Instead the direct and indirect impact is calculated separately and then combined. For the calculation of direct impact on natural forests I used the following equation: Con(“Rd_dist” > 5000, 1, (2.0 * ( Exp(-3.99998 + 1.093457 * Ln(“Rd_dist”) ) / (1 + Exp(-3.99998 + 1.093457 * Ln(“Rd_dist”)))) + 4.0) / 6.0) and for the direct impact of roads in non-forest natural areas I used: Con(“road_dist”) > 5000, 1, (2.0 * ( Exp(-8.861673 + 1.697327 * Ln(“road_dist”) ) / (1 + Exp(-8.861673 + 1.697327 * Ln(“road_dist”)))) + 4.0) / 6.0). Note that the /(+4.0/6.0) part is added to the equations because the cause-effect relation is only known for 2 species groups (birds and mammals) out of 6 species groups that would be needed to give a more representative result of the impact on biodiversity.

For the calculation of indirect infrastructure pressure around urban, agricultural and mining areas I used the following equation: exp(-0.25+0.000103 * Dist)/(1+exp(-0.25+0.000103 * Dist))

See for more detail on these calculations the paper:

The calculation of fragmentation in Mongolia is carried out for clusters of nature that are dissected by major roads and other land use. The relation by natural area and MSA_fragm is calculated via the following relation:

Cluster size                       MSA
0-1                                        0.35
1-10                                      0.45
10-100                                 0.65
100-1000                             0.9
1000-10000                         0.98
>=10000                              1

Nitrogen deposition
This pressure is in general absent in Mongolia. Only in the area near the capital city of Ulaan Baatar Nitrogen deposition will be high as air pollution is high due to traffic, coil stoves in the houses and the large coil fueled electricity plants. If a map of Nitrogen deposition had been acquired the following calculation would have been applied:  first calculating the exceedence of Nitrogen: N exeedence = Nitrogen deposition – Critical load. The cause-effect relations are known for three ecosystems: Arctic-Alpine ecosystem, Boreal coniferous forest and Grassland by applying resp the following equations: MSA_nitro = 0.9 – 0.05 NExceed; MSA_nitro  = 0.8 – 0.14 ln (NExceed); MSA_nitro  = 0.8 – 0.08 ln (NExceed). Global maps of Nitrogen deposition and Critical loads can be acquired freely from the Netherlands Environmental Assessment Agency.

However, detailed information on Nitrogen deposition around Ulaan Baatar was missing and therefore the impact of this pressure has been omitted for this assessment.

The impact of climate in Mongolia is calculated with help of information on global temperature increase (OECD) and known impact of temperature increase on 15 climate related biomes. Underneath the tables that I used for the calculation of climate change for the year 2007 in in Mongolia:

Temperature increase table (4 february 2014, OECD scenario)

Year      Degrees C
1970      0.241
1975      0.267
1980      0.353
1985      0.448
1990      0.558
1995      0.670
2000      0.777
2005      0.888
2010      1.005
2015      1.152
2020      1.325
2025      1.499
2030      1.680
2035      1.865
2040      2.053
2045      2.242
2050      2.433

Relation climate change and biome

Biome (climate)                                 New Slope Values (Slope (oC-1))
Ice                                                          3.56
Tundra                                                  4.26
Wooded tundra                                   4.26
Boreal forest                                        3.67
Cool conifer forest                            11.27
Temperate mixed forest                    4.87
Temperate deciduous forest             7.1
Warm mixed forest                           14.57
Grassland and steppe                       12.01
Hot desert / desert                             12.01
Scrubland                                                6.6
Savanna                                                   7.75
Tropical woodland                               10.75
Tropical forest                                       10.75
Mediterannean shrub                            6.61

The slopes in the above table have been used to calculate the MSA_clim for Mongolia: MSA_clim = 1 – (Slope * Δtemperature)/100.

Please note that the equations and assumptions used by me for the Mongolia assessment do not have to be the most recent ones. These are or will be mentioned with publication references on the official GLOBIO3 website:

I will let you know when a new publication is published on the website.

Please also share your experiences, assumptions and results of your GLOBO3 assessments on the Biodiversity Modelling Network (BMN) so that we can learn from each other’s experiences!

Kind regards,
Wilbert van Rooij


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